Introduction
Superframes is a scheme for frame-semantic annotation of text. Every predicate is assigned a frame, and every argument is assigned a role. Superframes annotations can help search corpora for phenomena of interest, enable quantitative cross-lingual comparisons, and support semantic parsing. Superframes aims to be easy to annotate. In particular,
- Superframes does not require a lexicon. Frames are coarse and small enough in number to learn them by heart.
- Superframes is language-independent.
- Superframes ia annotated atop Universal Dependencies, thus delegating many difficult syntax-related decisions to an established framework.
Superframes defines a taxonomy of frames, each of which denotes a relation between two entities and thus defines two roles. Annotating a text comes down to assigning frame labels to content words and role labels to UD dependency edges between them.
Annotating Static Verbs
Consider the following sentence (relevant UD edges shown):
Dependency graph for sentence: Kim owns a house.
Here, we say that the (verbal) predicate owns evokes the POSSESSION frame,
which defines the possessum and possessor roles. The possessum roles is
filled by a house and the possessor roles is filled by Kim. So we
annotate as follows:
Dependency graph for sentence: Kim owns a house. Token owns is labeled POSSESSION and has an edge labeled possessor to token Kim and an edge labeled possessum to token house.
We call the arguments that fill the predicate’s frame’s roles the core arguments. We will turn to non-core arguments later.
Note that semantic roles abstract away from syntactic alternation. As an example, consider the following passive sentence and its Superframes annotation:
Dependency graph for sentence: The house is owned by Kim.
Dependency graph for sentence: The house is owned by Kim. Token owned is labeled POSSESSION and has an edge labeled possessum to token house and an edge labeled possessor to token Kim.
Note also that there are only a few dozen superframes, so the meaning they specify is necessarily coarse. Different predicates with similar meaning can invoke the same superframe. This is a feature, as it makes explicit similar predicates and roles.
Dependency graph for sentence: The house belongs to Kim. Token belongs is labeled POSSESSION and has an edge labeled possessum to token house and an edge labeled possessor to token Kim.
Verbs with One Argument
There are, of course, also predicates with only one argument, in which case only one of the two roles is used (most often the first one).
Dependency graph for sentence: Kim is sleeping. Token sleeping is labeled INTERNAL-STATE and has an edge labeled has-state to token Kim.
INTERNAL-STATE is one of those superframes whose second role state is
rarely filled by an argument. It denotes an abstract entity (here: the state of
being asleep) that is already expressed by the predicate.
Verbs with Zero Arguments
It also happens that predicates occur with no core arguments. One example is weather verbs such as rain. It has a syntactic, but semantically empty subject, which is annotated with NONCOMP.
Important
Predicate occurrences with no core arguments must always be annotated with the most general superframe, ENTITY.
So this is what happens for raining:
Dependency graph for sentence: It is raining. Token raining is labeled ENTITY and has an edge labeled NONCOMP to token It.
Annotating Dynamic Verbs
While all superframes denote states, many predicates, especially verbs, do not simply denote a state. Rather, they denote an event.
Note
We refer to events and states collectively as eventualities or scenes for short.
Events are distinguished from states by their temporal structure. They progress through two or more stages, each of which is itself a state or, in fact, another event.
In Superframes, events are annotated using a number of special frames called aspectual frames. You first frame a stage (which is usually a state), and then you add an aspectual frame that indicates that the predicate evokes not the stage, but an event involving the stage. There are seven aspectual frames:
| Frame | Description | |
|---|---|---|
INIT | event works towards beginning of stage | |
DEINIT | event works towards end of stage | |
PREVENTION | event works against beginning of stage | |
CONTINUATION | stage continues throughout event | |
TRANSIT | stage begins and ends during event | |
HABIT | stage occurs regularly/usually during event | |
DYN | different stages may occur during event with any pattern |
Note
The frame for the stage is combined with the aspectual frame through a mechanism called stacking. We stack the aspectual frame on top of the stage frame by writing the two separated by a hyphen, meaning that the stage frame becomes the first argument of the aspectual frame. The first frame (also called the base frame) still determines the core roles that can be used.
Here is the mechanism illustrated for three different aspectual frames using
POSSESSION as stage frame:
Dependency graph for sentence: Kim got the house. Token got is labeled POSSESSION-INIT and has an edge labeled possessor to token Kim and an edge labeled possessum to token house.
Dependency graph for sentence: Kim lost the house. Token lost is labeled POSSESSION-DEINIT and has an edge labeled possessor to token Kim and an edge labeled possessum to token house.
Dependency graph for sentence: Kim kept the house. Token kept is labeled POSSESSION-CONTINUATION and has an edge labeled possessor to token Kim and an edge labeled possessum to token house.
And here it is illustrated for all the aspectual frames using LOCATION as
stage frame:
Dependency graph for sentence: The Empire State Building is located in New York. Token located is labeled LOCATION and has an edge labeled has-location to token Building and an edge labeled location to token York.
Dependency graph for sentence: Kim walked towards Boston. Token walked is labeled LOCATION-INIT and has an edge labeled has-location to token Kim and an edge labeled location to token Boston.
Dependency graph for sentence: The vase fell to the ground. Token fell is labeled LOCATION-INIT and has an edge labeled has-location to token vase and an edge labeled location to token ground.
Dependency graph for sentence: Kim left Boston. Token left is labeled LOCATION-DEINIT and has an edge labeled has-location to token Kim and an edge labeled location to token Boston.
Dependency graph for sentence: Kim stayed in Boston. Token stayed is labeled LOCATION-CONTINUATION and has an edge labeled has-location to token Kim and an edge labeled location to token Boston.
Dependency graph for sentence: Kim lives in Boston. Token lives is labeled LOCATION-HABIT and has an edge labeled has-location to token Kim and an edge labeled location to token Boston.
Dependency graph for sentence: The ball missed the target. Token missed is labeled LOCATION-PREVENTION and has an edge labeled has-location to token ball and an edge labeled location to token target.
Dependency graph for sentence: Kim went via Washingon. Token went is labeled LOCATION-TRANSIT and has an edge labeled has-location to token Kim and an edge labeled location to token Washingon.
Dependency graph for sentence: Kim travelled through Pittsburg. Token travelled is labeled LOCATION-TRANSIT and has an edge labeled has-location to token Kim and an edge labeled location to token Pittsburg.
Dependency graph for sentence: Kim followed the path. Token followed is labeled LOCATION-TRANSIT and has an edge labeled has-location to token Kim and an edge labeled location to token path.
Dependency graph for sentence: Kim walked. Token walked is labeled LOCATION-DYN and has an edge labeled has-location to token Kim.
Further examples include:
Dependency graph for sentence: The vase broke. Token broke is labeled INTERNAL-STATE-INIT and has an edge labeled has-state to token vase.
Dependency graph for sentence: Kim befriended Sandy. Token befriended is labeled SOCIAL-RELATION-INIT and has an edge labeled socially-related to token Kim and an edge labeled socially-related-to to token Sandy.
Dependency graph for sentence: Kim married Sandy. Token married is labeled SOCIAL-RELATION-INIT and has an edge labeled socially-related to token Kim and an edge labeled socially-related-to to token Sandy.
Dependency graph for sentence: Kim divorced Sandy. Token divorced is labeled SOCIAL-RELATION-DEINIT and has an edge labeled socially-related to token Kim and an edge labeled socially-related-to to token Sandy.
Dependency graph for sentence: Kim was saved from the dragon. Token saved is labeled INFLUENCE-PREVENTION and has an edge labeled affected to token Kim and an edge labeled influence to token dragon.
Dependency graph for sentence: Kim is partying. Token partying is labeled SITUATION-DYN and has an edge labeled situee to token Kim.
Stacking Aspectual Frames Onto Roles
Some predicates take multiple arguments wrt. different stages. For these cases, there is a special notation where you can stack an aspectual frame atop a role. For example:
Dependency graph for sentence: Kim traveled from Chicago via Pittsburgh to Boston. Token traveled is labeled LOCATION-INIT and has an edge labeled has-location to token Kim and an edge labeled location-DEINIT to token Chicago and an edge labeled location-TRANSIT to token Pittsburgh and an edge labeled location to token Boston.
Dependency graph for sentence: Kim sold Sandy the house. Token sold is labeled POSSESSION-DEINIT and has an edge labeled possessor to token Kim and an edge labeled possessor-INIT to token Sandy and an edge labeled possessum to token house.
Dependency graph for sentence: Sandy bought the house from Kim. Token bought is labeled POSSESSION-INIT and has an edge labeled possessor to token Sandy and an edge labeled possessum to token house and an edge labeled possessor-DEINIT to token Kim.
Dependency graph for sentence: Sandy owes Sandy money. Token owes is labeled POSSESSION-DEINIT-NECESSITY and has an edge labeled possessor to token Sandy and an edge labeled possessor-INIT to token Sandy and an edge labeled possessum to token money.
Using Aspectual Frames by Themselves
For predicates that only express aspect and nothing about the stage (which is instead denoted by an argument), aspectual frames can be used by themselves, without stacking:
Dependency graph for sentence: The concert began. Token began is labeled INIT and has an edge labeled initiated to token concert.
Dependency graph for sentence: The concert continued. Token continued is labeled CONTINUATION and has an edge labeled continued to token concert.
Dependency graph for sentence: The concert finished. Token finished is labeled DEINIT and has an edge labeled deinitiated to token concert.
Dependency graph for sentence: The shouting faded. Token faded is labeled DEINIT and has an edge labeled deinitiated to token shouting.
Dependency graph for sentence: A coup was attempted. Token attempted is labeled INIT and has an edge labeled initiated to token coup.
Dependency graph for sentence: An outbreak was prevented. Token prevented is labeled PREVENTION and has an edge labeled prevented to token outbreak.
Using Aspectual Frames with the META Frame
Some predicates share an argument with another argument in what is known as a
control construction. They are annotated with the special META
frame. Its scene role is filled by the embedded predicate, and its
participant role is filled by the controlled argument.
Important
If a predicate has a
participantand ascenedependent, then an additional dependency edge (not present in basic UD) must be present from thesceneto theparticipant. This edge is called a backlink. This rule is enforced automatically by the checker.
Often, control predicates express aspect while the embedded predicate expresses
a stage. Thus, stack an aspect frame onto META. For example:
Dependency graph for sentence: Kim started walking. Token started is labeled META-INIT and has an edge labeled participant to token Kim and an edge labeled scene to token walking. Token walking is labeled LOCATION-DYN and has an edge labeled has-location to token Kim.
Dependency graph for sentence: Kim stopped walking. Token stopped is labeled META-DEINIT and has an edge labeled participant to token Kim and an edge labeled scene to token walking. Token walking is labeled LOCATION-DYN and has an edge labeled has-location to token Kim.
Dependency graph for sentence: Kim kept walking. Token kept is labeled META-CONTINUATION and has an edge labeled participant to token Kim and an edge labeled scene to token walking. Token walking is labeled LOCATION-DYN and has an edge labeled has-location to token Kim.
Dependency graph for sentence: Kim refrained from walking. Token refrained is labeled META-PREVENTION and has an edge labeled participant to token Kim and an edge labeled scene to token walking. Token walking is labeled LOCATION-INIT and has an edge labeled has-location to token Kim.
Dependency graph for sentence: Kim used to walk. Token used is labeled META-HABIT-TIME and has an edge labeled participant to token Kim and an edge labeled scene to token walk. Token walk is labeled SITUATION-DYN and has an edge labeled situee to token Kim.
Dependency graph for sentence: Kim finished their work. Token finished is labeled META-DEINIT and has an edge labeled participant to token Kim and an edge labeled scene to token work. Token work is labeled SITUATION-DYN and has an edge labeled situee to token Kim.
Annotating Non-core Arguments
So far, we have only seen predicates with at most two arguments, all of whose roles are defined by the (base) frame that the predicate is annotated with. We call the base frame together with any frames stacked on top of it the core frame. But many verbs have more than two arguments, or otherwise arguments with roles from different frames. One very common example is causative subjects, denoting an entity presented as causing the situation denoted by the core frame. For example, consider the following:
Dependency graph for sentence: The vase broke. Token broke is labeled INTERNAL-STATE-INIT and has an edge labeled has-state to token vase.
Dependency graph for sentence: Kim broke the vase. Token broke is labeled INTERNAL-STATE-INIT and has an edge labeled CAUSER to token Kim and an edge labeled has-state to token vase.
In both sentences, the core frame is INTERNAL-STATE-INIT, with the vase as
the has-state argument. In the second sentence, Kim is added as another
argument, presented as the causer of the situation denoted by the core frame
(the breaking of the vase). We thus annotate it with the causer role from the
CAUSATION frame. To distinguish them from core arguments, non-core arguments
are written in all upper case.
Note
Adding a non-core role is interpreted as implicitly adding the corresponding frame, where the dependent fills the non-core role, and the core frame fills the other role. Thus, in the example, by adding
CAUSERas the non-core role, we implicitly add aCAUSATIONframe whosecauserrole is filled by Kim, and whoseeffectrole is filled by the breaking of the vase.
Similar examples include:
Dependency graph for sentence: Kim threw the vase to the ground. Token threw is labeled LOCATION-INIT and has an edge labeled CAUSER to token Kim and an edge labeled has-location to token vase and an edge labeled location to token ground.
Dependency graph for sentence: Kim gave Sandy a book. Token gave is labeled POSSESSION-INIT and has an edge labeled CAUSER to token Kim and an edge labeled possessor to token Sandy and an edge labeled possessum to token book.
Dependency graph for sentence: Alex introduced Kim to Sandy. Token introduced is labeled SOCIAL-RELATION-INIT and has an edge labeled CAUSER to token Alex and an edge labeled socially-related to token Kim and an edge labeled socially-related-to to token Sandy.
Dependency graph for sentence: The official married Kim to Sandy. Token married is labeled SOCIAL-RELATION-INIT and has an edge labeled CAUSER to token official and an edge labeled socially-related to token Kim and an edge labeled socially-related-to to token Sandy.
Dependency graph for sentence: Kim prevented Sandy from going. Token prevented is labeled META-PREVENTION and has an edge labeled CAUSER to token Kim and an edge labeled participant to token Sandy and an edge labeled scene to token going. Token going is labeled LOCATION-INIT and has an edge labeled has-location to token Sandy.
Dependency graph for sentence: Swift action prevented an outbreak. Token prevented is labeled PREVENTION and has an edge labeled CAUSER to token action and an edge labeled prevented to token outbreak.
Two other very common non-core arguments are the sender and recipients (experiencers) of messages.
Dependency graph for sentence: Kim talked to Sandy about Bali. Token talked is labeled MESSAGE-INIT and has an edge labeled SENDER to token Kim and an edge labeled EXPERIENCER to token Sandy and an edge labeled content to token Bali.
Dependency graph for sentence: I showed my masterpiece to the grown-ups. Token showed is labeled MESSAGE-INIT and has an edge labeled SENDER to token I and an edge labeled content to token masterpiece and an edge labeled EXPERIENCER to token grown-ups.
Other non-core arguments are usually rather predicate-specific.
Dependency graph for sentence: Kim searched the woods for Sandy. Token searched is labeled MESSAGE-INIT and has an edge labeled EXPERIENCER to token Kim and an edge labeled LOCATION to token woods and an edge labeled content to token Sandy.
Dependency graph for sentence: Kim bought the house for a million dollars. Token bought is labeled POSSESSION-INIT and has an edge labeled possessor to token Kim and an edge labeled possessum to token house and an edge labeled ASSET to token dollars.
Annotating Nouns and Pronouns
So far, we have only looked at verbal predicates. But nouns can have (core) arguments too. Specifically, this is true for event nouns and relational nouns.
Event nouns evoke eventualities (events or states). They are annotated much like verbs:
Dependency graph for sentence: Kim ’s breaking of the vase. Token breaking is labeled INTERNAL-STATE-INIT and has an edge labeled CAUSER to token Kim and an edge labeled has-state to token vase.
Dependency graph for sentence: Kim ’s height. Token height is labeled PROPERTY and has an edge labeled has-property to token Kim.
Dependency graph for sentence: Sandy ’s destruction. Token destruction is labeled EXISTENCE-DEINIT and has an edge labeled existent to token Sandy.
Dependency graph for sentence: Sandy ’s destruction of the city. Token destruction is labeled EXISTENCE-DEINIT and has an edge labeled CAUSER to token Sandy and an edge labeled existent to token city.
Dependency graph for sentence: the grown-ups’ response. Token response is labeled EXPRESSION and has an edge labeled sender to token grown-ups’.
Dependency graph for sentence: my life. Token life is labeled EXISTENCE and has an edge labeled existent to token my.
Dependency graph for sentence: my amazement. Token amazement is labeled EXPERIENCE and has an edge labeled experiencer to token my.
Dependency graph for sentence: my studies. Token studies is labeled EXPERIENCE-INIT and has an edge labeled experiencer to token my.
Dependency graph for sentence: his level. Token level is labeled PROPERTY and has an edge labeled has-property to token his.
Relational nouns also evoke eventualities. Additionally, they refer to one of the participants in the relation. Since we are not concerned with reference, we annotate relational nouns just like event nouns:
Dependency graph for sentence: Kim ’s friend. Token friend is labeled SOCIAL-RELATION and has an edge labeled socially-related to token Kim.
Dependency graph for sentence: my critic. Token critic is labeled EVALUATION and has an edge labeled evaluee to token my.
Dependency graph for sentence: a book about the primeval forest. Token book is labeled MESSAGE and has an edge labeled content to token forest.
Dependency graph for sentence: a copy of the drawing. Token copy is labeled COPY and has an edge labeled original to token drawing.
Dependency graph for sentence: their prey. Token prey is labeled SOCIAL-RELATION and has an edge labeled socially-related to token their.
Pronouns can function as event/relational pronouns, too. Annotate them like you would their antecedent:
Dependency graph for sentence: Kim saw the picture of the sheep , Sandy saw that of the boa. Token picture is labeled MESSAGE and has an edge labeled content to token sheep. Token that is labeled MESSAGE and has an edge labeled content to token boa.
Nouns and pronouns that are neither event (pro)nouns nor relational can’t have
any arguments. Thus, the rule that we mentioned
earlier applies: an
occurrence of a predicate without any core arguments is always annotated with
the special superframe ENTITY.
Dependency graph for sentence: a tree. Token tree is labeled ENTITY.
Dependency graph for sentence: Kim. Token Kim is labeled ENTITY.
Dependency graph for sentence: they. Token they is labeled ENTITY.
Annotating Adjuncts
Adjuncts are dependents of predicates that are not arguments – that is, they are not assigned a role by the predicate, but by the adjunct construction, often involving an adposition or a conjunction. All kinds of predicates can have adjuncts, including verbs, nouns, and others. Superframes does not try to distinguish between adjuncts and non-core arguments – we annotate the former just like the latter:
Dependency graph for sentence: a tree in the garden. Token tree is labeled ENTITY and has an edge labeled LOCATION:hl to token garden.
Dependency graph for sentence: Kim ’s tree. Token tree is labeled ENTITY and has an edge labeled POSSESSOR:hl to token Kim.
Dependency graph for sentence: my car. Token car is labeled ENTITY and has an edge labeled POSSESSOR:hl to token my.
Dependency graph for sentence: my feet. Token feet is labeled ENTITY and has an edge labeled WHOLE:hl to token my.
Dependency graph for sentence: Kim is sweating in the sauna. Token sweating is labeled CONTAINMENT-DEINIT and has an edge labeled container to token Kim and an edge labeled LOCATION:hl to token sauna.
Dependency graph for sentence: Wir machen das wegen der Kinder. Token machen is labeled CAUSATION and has an edge labeled causer to token Wir and an edge labeled effect to token das and an edge labeled REASON:hl to token Kinder.
Dependency graph for sentence: gekommen , um zu bleiben. Token gekommen is labeled LOCATION-INIT and has an edge labeled END:hl to token bleiben.
Dependency graph for sentence: after that they are not able to move. Token able is labeled META-POSSIBILITY and has an edge labeled TIME:hl to token that and an edge labeled participant to token they and an edge labeled scene to token move.
Attributive Adjectives and Adverbs
Attributive adjectives and adverbs behave syntactically like modifiers, but
they are also predicates assigning the modifiee a role. In fact, the semantic
relation that this modifier relation denotes is that the modifier evokes a
scene in which the modifiee participates. We have already encountered the frame
that encodes this relation in the chapter on Annotating Dynamic
Verbs:
it is called META. With attributive adjectives and adverbs, we use
its scene role as a non-core role, and we add a backlink for the role
assigned by the modifier to the modifiee.
Important
If a predicate has a
SCENEdependent, then an additional dependency edge (not present in basic UD) must be present from the dependent to the predicate. This edge is called a backlink. This rule is enforced automatically by the checker.
Dependency graph for sentence: a red car. Token red is labeled PROPERTY and has an edge labeled has-property:hl to token car. Token car is labeled ENTITY and has an edge labeled SCENE:hl to token red.
Dependency graph for sentence: the tired dog. Token tired is labeled INTERNAL-STATE and has an edge labeled has-state:hl to token dog. Token dog is labeled ENTITY and has an edge labeled SCENE:hl to token tired.
Dependency graph for sentence: ein anderes Plakat. Token anderes is labeled COMPARISON and has an edge labeled compared:hl to token Plakat. Token Plakat is labeled ENTITY and has an edge labeled SCENE:hl to token anderes.
Dependency graph for sentence: Kim ran fast. Token ran is labeled LOCATION-DYN and has an edge labeled has-location to token Kim and an edge labeled SCENE:hl to token fast. Token fast is labeled PROPERTY and has an edge labeled has-property:hl to token ran.
Dependency graph for sentence: Kim ran far. Token ran is labeled LOCATION-DYN and has an edge labeled has-location to token Kim and an edge labeled SCENE:hl to token far. Token far is labeled QUANTITY and has an edge labeled has-quantity:hl to token ran.
Dependency graph for sentence: Ich spiele lieber Schach. Token spiele is labeled META and has an edge labeled participant to token Ich and an edge labeled SCENE:hl to token lieber and an edge labeled scene to token Schach. Token lieber is labeled EVALUATION and has an edge labeled evaluee:hl to token spiele. Token Schach is labeled SITUATION-DYN and has an edge labeled situee to token Ich.
Dependency graph for sentence: Der ist sowieso kaputt. Token sowieso is labeled CONDITION and has an edge labeled has-condition:hl to token kaputt. Token kaputt is labeled INTERNAL-STATE and has an edge labeled has-state to token Der and an edge labeled SCENE:hl to token sowieso.
Dependency graph for sentence: Und doch sah er intelligent aus. Token doch is labeled CONCESSION and has an edge labeled asserted:hl to token sah. Token sah is labeled META-MESSAGE and has an edge labeled SCENE:hl to token doch and an edge labeled participant to token er and an edge labeled scene to token intelligent.
Dependency graph for sentence: Sie sprangen des Regens ungeachtet nach draußen. Token sprangen is labeled LOCATION-INIT and has an edge labeled has-location to token Sie and an edge labeled SCENE:hl to token ungeachtet and an edge labeled LOCATION to token draußen. Token ungeachtet is labeled CONCESSION and has an edge labeled asserted:hl to token sprangen and an edge labeled conceded to token Regens.
Dependency graph for sentence: Kim war unvermindert fröhlich. Token unvermindert is labeled QUANTITY-CONTINUATION and has an edge labeled has-quantity:hl to token fröhlich. Token fröhlich is labeled INTERNAL-STATE and has an edge labeled has-state to token Kim and an edge labeled SCENE:hl to token unvermindert.
Dependency graph for sentence: » Wir haben um Hilfe gebeten « , so Saqib. Token gebeten is labeled NORM and has an edge labeled SENDER to token Wir and an edge labeled norm-content to token Hilfe and an edge labeled SCENE:hl to token so. Token so is labeled EXPRESSION and has an edge labeled sent:hl to token gebeten and an edge labeled sender to token Saqib.
Dependency graph for sentence: The little prince flashed back at me. Token flashed is labeled EXPRESSION-INIT and has an edge labeled SENDER to token prince and an edge labeled SCENE:hl to token back. Token back is labeled REACTION and has an edge labeled reaction:hl to token flashed.
Dependency graph for sentence: He went on : “ You mix everything up together … ”. Token went is labeled MESSAGE-INIT and has an edge labeled SENDER to token He and an edge labeled SCENE:hl to token on and an edge labeled content to token mix. Token on is labeled CONTINUATION and has an edge labeled continued:hl to token went.
Relative Clauses
Relative clauses work very similarly to attributive adjectives and adverbs:
they modify a predicate (usually a noun), but also act as predicates assigning
that noun a role. Again, we use SCENE and add a backlink to the modified
noun.
Dependency graph for sentence: the man that I talked to. Token man is labeled ENTITY and has an edge labeled SCENE to token talked. Token talked is labeled EXPRESSION-DYN and has an edge labeled EXPERIENCER:hl to token man and an edge labeled EXPERIENCER to token that and an edge labeled sender to token I and an edge labeled EXPERIENCER to token to.
Dependency graph for sentence: the man I talked to. Token man is labeled ENTITY and has an edge labeled SCENE to token talked. Token talked is labeled EXPRESSION-DYN and has an edge labeled EXPERIENCER:hl to token man and an edge labeled sender to token I and an edge labeled EXPERIENCER to token to.
Note that relative pronouns and stranded prepositions are annotated with the same role as the antecedent.
Note also that relative clauses need not be finite, but can, e.g., be headed by participles:
Dependency graph for sentence: the song liked by Kim. Token song is labeled ENTITY and has an edge labeled SCENE to token liked. Token liked is labeled EVALUATION and has an edge labeled evaluee:hl to token song and an edge labeled EXPERIENCER to token Kim.
Dependency graph for sentence: students living on campus. Token students is labeled ENTITY and has an edge labeled SCENE to token living. Token living is labeled LOCATION-HABIT and has an edge labeled has-location:hl to token students and an edge labeled location to token campus.
Dependency graph for sentence: without anything to lead up to it. Token anything is labeled ENTITY and has an edge labeled SCENE to token lead. Token lead is labeled SEQUENCE and has an edge labeled followed:hl to token anything and an edge labeled follows to token it.
Dependency graph for sentence: the man to talk to. Token man is labeled ENTITY and has an edge labeled SCENE-NECESSITY to token talk and an edge labeled EXPERIENCER to token to. Token talk is labeled EXPRESSION and has an edge labeled EXPERIENCER:hl to token man.
Dependency graph for sentence: sterbender Schwan. Token sterbender is labeled EXISTENCE-DEINIT and has an edge labeled existent:hl to token Schwan. Token Schwan is labeled ENTITY and has an edge labeled SCENE to token sterbender.
Dependency graph for sentence: gedeckter Tisch. Token gedeckter is labeled CONTACT-INIT and has an edge labeled surface:hl to token Tisch. Token Tisch is labeled ENTITY and has an edge labeled SCENE to token gedeckter.
Note also that the backlink need not go directly from the head of the relative clause, but can also have a more deeply embedded source:
Dependency graph for sentence: eine Gestalt , deren Magerkeit durch den Trainingsanzug noch betont wurde. Token Gestalt is labeled ENTITY and has an edge labeled SCENE to token betont. Token Magerkeit is labeled PROPERTY and has an edge labeled has-property:hl to token Gestalt and an edge labeled has-property to token deren. Token noch is labeled ACCOMPANIMENT and has an edge labeled accompanier to token betont. Token betont is labeled MESSAGE and has an edge labeled content to token Magerkeit and an edge labeled SENDER to token Trainingsanzug and an edge labeled SCENE to token noch.
Dependency graph for sentence: Atmosphäre , mit der sie sich zu umgeben wusste. Token Atmosphäre is labeled ENTITY and has an edge labeled SCENE to token wusste. Token umgeben is labeled SITUATION-INIT and has an edge labeled situator:hl to token Atmosphäre and an edge labeled situator to token der and an edge labeled CAUSER to token sie and an edge labeled situee to token sich. Token wusste is labeled META-POSSIBILITY and has an edge labeled participant to token sie and an edge labeled scene to token umgeben.
Relation Nominal Adjuncts
Relational nouns can likewise function as adjuncts assigning the modifiee a role. If there is an adposition, its semantic contribution is weak.
Dependency graph for sentence: In spite of all the good will , he came to doubt her. Token spite is labeled CONCESSION and has an edge labeled conceded to token will and an edge labeled asserted:hl to token came. Token came is labeled META-INIT and has an edge labeled SCENE:hl to token spite and an edge labeled participant to token he and an edge labeled scene to token doubt.
Annotating Nonverbal Clauses
In the prototypical clause, the head is a verb. But there are also clauses where other kinds of predicates function as the head. We distinguish four types of such clauses: adjectival clauses, identificational clauses, nominal clauses, and oblique clauses.
Adjectival Clauses
The head of an adjectival clause is an adjective that assigns the subject a role.
Dependency graph for sentence: My car is red. Token red is labeled PROPERTY and has an edge labeled has-property:hl to token car.
Dependency graph for sentence: The dog is tired. Token tired is labeled INTERNAL-STATE and has an edge labeled has-state:hl to token dog.
Dependency graph for sentence: Change is necessary. Token necessary is labeled NECESSITY and has an edge labeled necessary:hl to token Change.
Dependency graph for sentence: Change is possible. Token possible is labeled POSSIBILITY and has an edge labeled possible:hl to token Change.
Dependency graph for sentence: They are not able to move. Token able is labeled META-POSSIBILITY and has an edge labeled participant:hl to token They and an edge labeled SCENE to token not and an edge labeled scene to token move.
Identificational Clauses
An identificational clause expresses that the subject refers to the same entity as the head. Use SAME:
Dependency graph for sentence: The picture was that of the boa. Token that is labeled MESSAGE and has an edge labeled SAME:hl to token picture and an edge labeled content to token boa.
Dependency graph for sentence: The planet from which the little prince came is the asteroid known as B-612. Token asteroid is labeled ENTITY and has an edge labeled SAME:hl to token planet and an edge labeled SCENE to token known.
Nominal Clauses
The head of a nominal clause is a noun (or pronoun) that denotes a class of entities that the subject is said to be an instance of. If the noun is relational, it assigns the subject a role:
Dependency graph for sentence: He is our physics teacher. Token teacher is labeled MESSAGE-INIT-HABIT and has an edge labeled SENDER:hl to token He and an edge labeled EXPERIENCER to token our and an edge labeled content to token physics.
Dependency graph for sentence: She is the president of our club. Token president is labeled BOND and has an edge labeled tied:hl to token She and an edge labeled tied-to to token club.
Dependency graph for sentence: Sandy is the destroyer of the city. Token destroyer is labeled EXISTENCE-DEINIT and has an edge labeled CAUSER:hl to token Sandy and an edge labeled existent to token city.
Dependency graph for sentence: That is my fault. Token fault is labeled CAUSATION and has an edge labeled effect:hl to token That and an edge labeled causer to token my.
Otherwise, use INSTANCE:
Dependency graph for sentence: It was a picture of a boa constrictor. Token picture is labeled MESSAGE and has an edge labeled INSTANCE:hl to token It.
Dependency graph for sentence: Baobabs were not little bushes. Token bushes is labeled ENTITY and has an edge labeled INSTANCE:hl to token Baobabs and an edge labeled SCENE to token not and an edge labeled SCENE to token little.
Oblique Clauses
The head of an oblique clause is marked (e.g., by an adposition, a conjunction, or by case marking) in a way that expresses a semantic relation between the subject and the head. Accordingly, the subject is assigned a non-core role:
Dependency graph for sentence: The sprout was not like any other small sprouts on his planet. Token sprouts is labeled ENTITY and has an edge labeled COMPARED:hl to token sprout and an edge labeled SCENE to token not and an edge labeled SCENE to token other and an edge labeled SCENE to token small and an edge labeled LOCATION to token planet.
Dependency graph for sentence: Kim is at home. Token home is labeled ENTITY and has an edge labeled HAS-LOCATION:hl to token Kim.
Dependency graph for sentence: That house is Kim 's. Token Kim is labeled ENTITY and has an edge labeled POSSESSUM:hl to token house.
Dependency graph for sentence: That is because he is thinking of something else. Token thinking is labeled MESSAGE-DYN and has an edge labeled HAS-REASON:hl to token That and an edge labeled EXPERIENCER to token he and an edge labeled content to token something.
Dependency graph for sentence: This asteroid has only once been seen through the telescope . That was by a Turkish astronomer , in 1909 .. Token That is labeled EXPERIENCE. Token astronomer is labeled ENTITY and has an edge labeled EXPERIENCED:hl to token That and an edge labeled SCENE to token Turkish and an edge labeled TIME to token 1909.
Annotating Nonlocal Dependencies
Nonlocal dependencies are dependencies from one clause into another. They do
not exist as syntactic dependencies in (basic) UD, so for Superframes
annotation, we add them when needed. We have already seen nonlocal dependencies
with the META frame in the chapter on Annotating Dynamic
Verbs and with attributive adjectives, adverbs,
relative clauses, and relation nominal adjuncts in the chapter on Annotating
Adjuncts. In both cases, the element filling the
scene role has an additional dependency (a “backlink”) pointing back at the
element filling the participant role.
There are a number of other constructions that systematically introduce nonlocal dependencies, which we also annotate. We give examples of each in the following.
Subject Control
Dependency graph for sentence: Kim promised Sandy to come. Token promised is labeled META-NORM-INIT and has an edge labeled participant to token Kim and an edge labeled EXPERIENCER to token Sandy and an edge labeled scene to token come. Token come is labeled LOCATION-INIT and has an edge labeled has-location:hl to token Kim.
Dependency graph for sentence: Kim used a hammer to smash the vase. Token used is labeled META and has an edge labeled participant to token Kim and an edge labeled MEANS to token hammer and an edge labeled scene to token smash. Token smash is labeled INTERNAL-STATE-INIT and has an edge labeled CAUSER:hl to token Kim and an edge labeled has-state to token vase.
Dependency graph for sentence: Kim wants to swim. Token wants is labeled META-NORM and has an edge labeled participant to token Kim and an edge labeled scene to token swim. Token swim is labeled LOCATION-DYN and has an edge labeled has-location:hl to token Kim.
Dependency graph for sentence: Kim is hard to love. Token hard is labeled META-PREVENTION and has an edge labeled participant to token Kim and an edge labeled scene to token love. Token love is labeled EVALUATION and has an edge labeled evaluee:hl to token Kim.
Dependency graph for sentence: Kim is loath to leave. Token loath is labeled META-NEG-NORM and has an edge labeled participant to token Kim and an edge labeled scene to token leave. Token leave is labeled LOCATION-DEINIT and has an edge labeled has-location:hl to token Kim.
Dependency graph for sentence: This is all you need. Token all is labeled LIMIT and has an edge labeled limit to token This and an edge labeled limited to token need. Token need is labeled SITUATION-NECESSITY and has an edge labeled situator:hl to token This and an edge labeled situee to token you.
Object Control
Dependency graph for sentence: Kim persuaded Sandy to come. Token persuaded is labeled META-INIT and has an edge labeled SENDER to token Kim and an edge labeled participant to token Sandy and an edge labeled scene to token come. Token come is labeled LOCATION-INIT and has an edge labeled has-location:hl to token Sandy.
Dependency graph for sentence: Kim helped Sandy smash the vase. Token helped is labeled META-INIT and has an edge labeled CAUSER to token Kim and an edge labeled participant to token Sandy and an edge labeled scene to token smash. Token smash is labeled INTERNAL-STATE-INIT and has an edge labeled CAUSER to token Sandy and an edge labeled has-state to token vase.
Dependency graph for sentence: Kim wants Sandy to swim. Token wants is labeled META-NORM and has an edge labeled EXPERIENCER to token Kim and an edge labeled participant to token Sandy and an edge labeled scene to token swim. Token swim is labeled LOCATION-DYN and has an edge labeled has-location:hl to token Sandy.
Light Verbs
From the perspective of Superframes, light verbs are just control verbs whose
scene role happens to be filled by a noun. For details and examples, see
META.
“Non-obligatory” Control
Here, the control relationship is contributed by an adjunct construction rather than by the predicate.
Dependency graph for sentence: Kim left after trashing the room. Token left is labeled LOCATION-DEINIT and has an edge labeled has-location to token Kim and an edge labeled TIME to token trashing. Token trashing is labeled INTERNAL-STATE-INIT and has an edge labeled CAUSER:hl to token Kim and an edge labeled has-state to token room.
Dependency graph for sentence: Kim has come to stay. Token come is labeled LOCATION-INIT and has an edge labeled has-location to token Kim and an edge labeled END to token stay. Token stay is labeled LOCATION-CONTINUATION and has an edge labeled has-location:hl to token Kim.
Dependency graph for sentence: The little prince asked me abruptly , as if seized by a grave doubt .... Token asked is labeled MESSAGE-INIT and has an edge labeled SENDER to token prince and an edge labeled REFERENCE to token seized. Token seized is labeled META-INIT and has an edge labeled participant:hl to token prince and an edge labeled scene to token doubt.
Dependency graph for sentence: Stop drawing sheep , whether small or big. Token Stop is labeled META-DEINIT and has an edge labeled scene to token drawing and an edge labeled CONDITION to token small and an edge labeled CONDITION to token big. Token drawing is labeled MESSAGE-INIT and has an edge labeled content to token sheep. Token small is labeled PROPERTY and has an edge labeled has-property:hl to token sheep. Token big is labeled PROPERTY and has an edge labeled has-property:hl to token sheep.
Dependency graph for sentence: Some people , though short , reach amazing heights. Token short is labeled PROPERTY and has an edge labeled has-property:hl to token people. Token reach is labeled META-INIT and has an edge labeled participant to token people and an edge labeled CONCEDED to token short and an edge labeled scene to token heights. Token amazing is labeled PROPERTY and has an edge labeled has-property to token heights. Token heights is labeled PROPERTY and has an edge labeled has-property to token people.
Non-obligatory Control with Parasitic Gap
Dependency graph for sentence: the question we raised without answering. Token question is labeled ENTITY and has an edge labeled SCENE to token raised. Token raised is labeled MESSAGE-INIT and has an edge labeled message2 to token question and an edge labeled SENDER to token we and an edge labeled ACCOMPANIER-NEG to token answering. Token answering is labeled MESSAGE-INIT and has an edge labeled content:hl to token question and an edge labeled SENDER:hl to token we.
Depictives
Depicitves are like non-obligatory control, but without a conjunction and with
role ACCOMPANIER.
Dependency graph for sentence: Kim entered the room singing. Token entered is labeled LOCATION-INIT and has an edge labeled has-location to token Kim and an edge labeled location to token room and an edge labeled ACCOMPANIER to token singing. Token singing is labeled EXPRESSION and has an edge labeled sender:hl to token Kim.
Dependency graph for sentence: Kim ate the radish raw. Token ate is labeled CONTAINMENT-INIT and has an edge labeled container to token Kim and an edge labeled contained to token radish and an edge labeled ACCOMPANIER to token raw. Token raw is labeled INTERNAL-STATE and has an edge labeled has-state:hl to token radish.
Resultatives
Resultatives are like non-obligatory control, but without a conjunction and
with role EFFECT, and sometimes AFFECTED if there is no other role assigned
by the matrix predicate to the controlled argument.
Dependency graph for sentence: He took a whole herd of elephants away with him. Token took is labeled LOCATION-DEINIT and has an edge labeled CAUSER to token He and an edge labeled has-location to token herd and an edge labeled EFFECT to token away and an edge labeled ACCOMPANIED to token him. Token away is labeled LOCATION-DEINIT and has an edge labeled has-location:hl to token herd.
Dependency graph for sentence: I would bring myself down to his level. Token bring is labeled META-INIT and has an edge labeled participant to token myself and an edge labeled scene to token down. Token down is labeled PROPERTY-INIT and has an edge labeled has-property to token myself and an edge labeled EFFECT to token level. Token level is labeled PROPERTY and has an edge labeled has-property:hl to token myself and an edge labeled has-property to token his.
Dependency graph for sentence: You ’re talking me silly. Token talking is labeled EXPRESSION and has an edge labeled sender to token You and an edge labeled AFFECTED to token me and an edge labeled EFFECT to token silly. Token silly is labeled INTERNAL-STATE and has an edge labeled has-state:hl to token me.
Dependency graph for sentence: Kim sneezed the napkin off the table. Token sneezed is labeled CONTAINMENT-DEINIT and has an edge labeled container to token Kim and an edge labeled AFFECTED to token napkin and an edge labeled EFFECT to token table. Token table is labeled ENTITY and has an edge labeled HAS-LOCATION-DEINIT:hl to token napkin.
Dependency graph for sentence: She went out into the world all rumpled. Token went is labeled LOCATION-INIT and has an edge labeled has-location to token She and an edge labeled EFFECT to token out and an edge labeled location to token world and an edge labeled ACCOMPANIER to token rumpled. Token out is labeled LOCATION-INIT and has an edge labeled has-location:hl to token went.
Raising
Dependency graph for sentence: Kim seemed to fly. Token seemed is labeled META-MESSAGE and has an edge labeled participant to token Kim and an edge labeled scene to token fly. Token fly is labeled LOCATION-DYN and has an edge labeled has-location:hl to token Kim.
Attributive Adjective/Adverb/Relative Clause/Relation Nominal Adjunct
See the chapter on Annotating Adjuncts.
Pseudocleft
Dependency graph for sentence: This is what you need. Token what is labeled META and has an edge labeled participant to token This and an edge labeled scene to token need. Token need is labeled SITUATION-NECESSITY and has an edge labeled situator:hl to token This and an edge labeled situee to token you.
Dependency graph for sentence: For what the king fundamentally insisted upon was that his authority should be respected. Token what is labeled META and has an edge labeled scene to token insisted and an edge labeled participant to token respected. Token insisted is labeled NORM and has an edge labeled SENDER to token king and an edge labeled SCENE to token fundamentally and an edge labeled norm-content:hl to token respected.
Dependency graph for sentence: all you need to do is move your chair. Token all is labeled LIMIT and has an edge labeled limited to token need and an edge labeled limit to token move. Token need is labeled META-NECESSITY and has an edge labeled participant to token you and an edge labeled scene to token do. Token do is labeled META-INIT and has an edge labeled participant to token you and an edge labeled scene:hl to token move. Token move is labeled LOCATION-INIT and has an edge labeled CAUSER to token you and an edge labeled has-location to token chair.
It-cleft
Dependency graph for sentence: It was through words that everything was revealed to me. Token words is labeled ENTITY and has an edge labeled SCENE to token revealed. Token revealed is labeled MESSAGE-INIT and has an edge labeled MEANS:hl to token words and an edge labeled content to token everything and an edge labeled EXPERIENCER to token me.
Intra-Argument Relations
If an argument is introduced by an argument structure construction and semantically related to another argument rather than to the predicate, use REGARD.
Coordination
Dependency graph for sentence: ein sogenannter Televisor oder Hörsehschirm. Token sogenannter is labeled IDENTIFIER and has an edge labeled identified to token Televisor and an edge labeled identified:hl to token Hörsehschirm. Token Televisor is labeled ENTITY and has an edge labeled SCENE to token sogenannter. Token Hörsehschirm is labeled ENTITY and has an edge labeled SCENE:hl to token sogenannter.
Annotating Multiword Predicates
Multiword predicates
are predicates that consist of multiple words. They include light verb
constructions, which we annotate with the META frame. Other
dependents that do not fill a role of the head predicate but rather are part of
the predicate – as in verbal idioms, weather verbs, existential there, names,
other fixed expressions, or specialized sublanguages for such things as dates
and times – are marked with NONCOMP:
Dependency graph for sentence: Kim kicked the bucket. Token kicked is labeled EXISTENCE-DEINIT and has an edge labeled existent to token Kim and an edge labeled NONCOMP to token bucket.
Dependency graph for sentence: It is raining. Token raining is labeled ENTITY and has an edge labeled NONCOMP to token It.
Dependency graph for sentence: There was a famine. Token was is labeled META and has an edge labeled NONCOMP to token There and an edge labeled scene to token famine.
Dependency graph for sentence: the asteroid known as B 612. Token 612 is labeled ENTITY and has an edge labeled NONCOMP to token B.
Dependency graph for sentence: One drawing goes along all right. Token goes is labeled SITUATION-DYN and has an edge labeled situee to token drawing and an edge labeled NONCOMP to token along and an edge labeled SCENE to token right.
Dependency graph for sentence: “ It is a question of discipline , ” the little prince said to me later on. Token on is labeled TIME and has an edge labeled has-time to token said and an edge labeled NONCOMP to token later.
In some cases, the arguments of a multiword predicate depend on different
components. If the component heads a core argument of the multiword predicate,
give it the same frame as the head component. Otherwise, use ENTITY.
Dependency graph for sentence: I had the sheep to thank for it. Token had is labeled CAUSATION and has an edge labeled AFFECTED to token I and an edge labeled causer to token sheep and an edge labeled NONCOMP to token thank. Token thank is labeled CAUSATION and has an edge labeled effect to token it.
Dependency graph for sentence: I jumped to my feet. Token jumped is labeled POSE-INIT and has an edge labeled has-pose to token I and an edge labeled has-pose to token my and an edge labeled NONCOMP to token feet. Token feet is labeled POSE-INIT.
Dependency graph for sentence: Are you pulling my leg. Token pulling is labeled EXPRESSION-INIT and has an edge labeled sender to token you and an edge labeled NONCOMP to token leg. Token leg is labeled ENTITY and has an edge labeled EXPERIENCER to token my.
Light Verb Constructions vs. Verbal Idioms
Sometimes the borders between light verb constructions and verbal idioms are blurry. As a general rule, you should treat them as light verb predicates only if the dependent noun denotes the same kind of eventuality as the whole predicate. Otherwise, treat it as a verbal idiom.
For example, (to) do somebody a favor is a light verb predicate whereas (to) do somebody a kindness is not, because while both denote a favor, so does the noun favor by itself whereas kindness does not.
Dependency graph for sentence: Do me that favor. Token Do is labeled META-INIT and has an edge labeled participant to token me and an edge labeled scene to token favor. Token favor is labeled INFLUENCE and has an edge labeled affected to token me.
Dependency graph for sentence: Do me that kindness. Token Do is labeled INFLUENCE-INIT and has an edge labeled affected to token me and an edge labeled NONCOMP to token kindness. Token kindness is labeled ENTITY.
Bound Pronouns
Bound pronouns that are part of multiword predicates (e.g., inherently reflexive verbs) are annotated with the same role as their antecedent:
Dependency graph for sentence: Kim erinnert sich nicht daran. Token erinnert is labeled MESSAGE and has an edge labeled EXPERIENCER to token Kim and an edge labeled EXPERIENCER to token sich and an edge labeled SCENE to token nicht and an edge labeled content to token daran. Token nicht is labeled NEG and has an edge labeled negated to token erinnert.
Dependency graph for sentence: I address myself to you. Token address is labeled EXPRESSION-INIT and has an edge labeled sender to token I and an edge labeled sender to token myself and an edge labeled EXPERIENCER to token you.
Dependency graph for sentence: I had with me neither a mechanic nor any passenger. Token had is labeled ACCOMPANIMENT and has an edge labeled accompanied to token I and an edge labeled accompanied to token me and an edge labeled accompanier to token mechanic and an edge labeled accompanier to token passenger.
Exocentric Predicates
Occasionally, there is no (direct) syntactic connection between the components of a multiword predicate. For example as … as … could be analyzed as a predicate with two components, as could too … to …. We do not currently have a way to mark this, so we just annotate the parts as if each part were a full predicate.
Dependency graph for sentence: as soon as possible. Token as is labeled COMPARISON and has an edge labeled compared to token soon. Token as is labeled COMPARISON and has an edge labeled reference to token possible.
Dependency graph for sentence: I was born at the same moment as the sun. Token born is labeled EXISTENCE-INIT and has an edge labeled existent to token I and an edge labeled TIME to token moment and an edge labeled SAME to token sun. Token same is labeled IDENTITY and has an edge labeled same to token moment.
Dependency graph for sentence: I was too young to know how to love her. Token too is labeled QUANTITY and has an edge labeled has-quantity to token young. Token young is labeled AGE and has an edge labeled has-age to token I and an edge labeled REFERENCE to token know.
Principles for Annotation
Prefer Core Roles over Non-core Roles
Thus:
Dependency graph for sentence: Kim bought a house. Token bought is labeled POSSESSION-INIT and has an edge labeled possessor to token Kim and an edge labeled possessum to token house.
Dependency graph for sentence: Kim wants to swim. Token wants is labeled META-NORM and has an edge labeled participant to token Kim and an edge labeled scene to token swim.
Rather than:
Dependency graph for sentence: Kim bought a house. Token bought is labeled POSSESSION-INIT and has an edge labeled CAUSER to token Kim and an edge labeled possessum to token house.
Dependency graph for sentence: Kim wants to swim. Token wants is labeled META-NORM and has an edge labeled EXPERIENCER to token Kim and an edge labeled scene to token swim.
Try Adding Arguments
When not sure how to frame a predicate, it can help to think of additional
arguments that the predicate could have and that are just not realized in this
instance. For example, what is the role of It in It is not important? If we
add an argument, we might get It is not important for the process, where
INFLUENCE seems to fit with It as influence and the
process as affected. Thus:
Dependency graph for sentence: It is not important ( for the process ). Token not is labeled NEG and has an edge labeled negated to token important. Token important is labeled INFLUENCE and has an edge labeled influence to token It and an edge labeled SCENE to token not and an edge labeled affected to token process.
Similarly:
Dependency graph for sentence: She adjusted her petals ( to how she liked them ). Token adjusted is labeled COMPARISON-INIT and has an edge labeled CAUSER to token She and an edge labeled compared to token petals and an edge labeled reference to token liked.
Dependency graph for sentence: Sandy painted the kitchen ( with brown paint ). Token painted is labeled CONTACT-INIT and has an edge labeled CAUSER to token Sandy and an edge labeled surface to token kitchen and an edge labeled ornament to token paint.
Dependency graph for sentence: Kim seems happy ( to Sandy ). Token seems is labeled META-MESSAGE and has an edge labeled participant to token Kim and an edge labeled scene to token happy and an edge labeled EXPERIENCER to token Sandy.
Alternative Framings
Often, both a literal and a more figurative reading of a predicate are salient
and compete for the framing. You can annotate both possibilities: separate the
literal and the figurative frame/role by the symbol >>.
Dependency graph for sentence: One loves the sun when one is so sad. Token loves is labeled EVALUATION and has an edge labeled EXPERIENCER to token One and an edge labeled evaluee to token sun and an edge labeled TIME>>CONDITION to token sad.
Dependency graph for sentence: some sort of miraculous apparition must emerge from the bud. Token emerge is labeled LOCATION-DEINIT>>INIT and has an edge labeled has-location>>initiated to token apparition and an edge labeled location>>CAUSER to token bud.
Dependency graph for sentence: Embarassed , she coughed two or three times. Token coughed is labeled CONTAINMENT-DEINIT>>EXPRESSION and has an edge labeled ACCOMPANIER to token Embarassed and an edge labeled container>>sender to token she and an edge labeled TIME to token times.
Dependency graph for sentence: until some one among them is seized with the desire to awaken. Token seized is labeled POSSESSION-INIT>>META-INIT and has an edge labeled possessum>>participant to token one and an edge labeled possessor>>scene to token desire.
If two framings seems equally plausible to you and are not in a
literal-figurative relationship, use || instead of >>.
Use Comments if Not Sure
You are encouraged to use comments to note down any doubts and thoughts.
Comments can be added to the end of any line using the # symbol:
[TIME] generally (19) # ?
[has-time] fair (20)
[has-time] to - middling (24)
Obliqueness
Some predicates, such as friend or identical, denote an inherently symmetric relationship. Thus, their arguments are semantically virtually indistinguishable. In such cases, we default to giving the syntactically less oblique realized argument the first role, and the more oblique one, if any, the second. For our purposes, obliqueness is defined as follows:
| Obliqueness | Syntactic role | Dependency label |
|---|---|---|
| least oblique | subject | nsubj |
| direct object | obj | |
| indirect object | iobj | |
| most oblique | oblique nominal, nominal modifier | obl, nmod |
Thus we have, e.g.:
Dependency graph for sentence: Kim 's friend. Token friend is labeled BOND and has an edge labeled tied to token Kim.
Dependency graph for sentence: I am Kim 's friend. Token friend is labeled BOND and has an edge labeled tied to token I and an edge labeled tied-to to token Kim.
Dependency graph for sentence: Kim is comparing apples with oranges. Token comparing is labeled COMPARISON-MESSAGE-INIT and has an edge labeled EXPERIENCER to token Kim and an edge labeled compared to token apples and an edge labeled reference to token oranges.
Terminology
This is a list of terms and how they are used in this manual (not necessarily in linguistics in general, though I try to be compatible with widespread usage).
| Term | Explanation |
|---|---|
| adjunct | D is an adjunct of H if D is a dependent of H and not an argument, thus is assigned a role not by H but only by the adjunct construction – this means it must have a non-core role |
| argument | D is an argument of H if D is a dependent of H and is assigned a role by it – this can be a core role or a non-core role |
| dependent | if D, H are predicates, D is said to be a dependent of H if there is an edge from D to H in the annotation (either syntactic or non-syntactic) |
| event | a synonym for eventuality; sometimes also used as a synonym for process; I try to avoid the term due to its ambiguity |
| eventuality | a state or process |
| head | H is a head of D iff D is a dependent of H |
| predicate | a content word (noun, verb, adjective, or adverb) that evokes a frame |
| process | a dynamic eventuality, i.e., a transition over time through two or more states |
| scene | a synonym for eventuality |
| situation | a synonym for eventuality |
| state | a static eventuality, thus a state of affairs that does not include change over time |
Extended Examples
Here we show the annotation of some full sentences:
Dependency graph for sentence: I was very surprised to see a light break over the face of my young judge .. Token very is labeled QUANTITY and has an edge labeled has-quantity to token surprised. Token surprised is labeled EVALUATION and has an edge labeled EXPERIENCER to token I and an edge labeled SCENE to token very and an edge labeled evaluee to token see. Token see is labeled META-MESSAGE and has an edge labeled EXPERIENCER to token I and an edge labeled participant to token light and an edge labeled scene to token break. Token break is labeled EXPRESSION-INIT and has an edge labeled NONCOMP to token light and an edge labeled sender to token face. Token face is labeled ENTITY and has an edge labeled WHOLE to token judge. Token young is labeled AGE and has an edge labeled has-age to token judge. Token judge is labeled EVALUATION and has an edge labeled evaluee to token my and an edge labeled SCENE to token young.
ENTITY
This is the top of the superframe hierarchy, i.e., the most general frame. It is also the only frame that defines 0 rather than 2 roles. It is used for all those and only those occurrences of content words that do not have any core arguments, including all pronouns and all proper names.
Dependency graph for sentence: Chapter 1. Token Chapter is labeled ENTITY and has an edge labeled SCENE to token 1. Token 1 is labeled RANK and has an edge labeled has-rank to token Chapter.
Dependency graph for sentence: I. Token I is labeled ENTITY.
Dependency graph for sentence: a magnificent picture. Token magnificent is labeled PROPERTY and has an edge labeled has-property to token picture. Token picture is labeled ENTITY and has an edge labeled SCENE to token magnificent.
Dependency graph for sentence: an animal. Token animal is labeled ENTITY.
Dependency graph for sentence: a drawing. Token drawing is labeled ENTITY.
Dependency graph for sentence: Kim. Token Kim is labeled ENTITY.
Note that we go strictly by occurrence: the same word in another context may well have core arguments and thus be framed differently.
Dependency graph for sentence: a drawing of an elephant. Token drawing is labeled MESSAGE and has an edge labeled content to token elephant.
SITUATION
Roles: situee, situator
This superframe is the ancestor of all other superframes except ENTTIY. It
denotes a situation in the most general sense: some entity (the situee) is in
a situation, whatever the nature of that situation may be. If there is another
core argument, it is labeled situator and the situation is then some sort of
relation between two entities. There are four usual ways to use this frame:
Stacked with -DYN
Used for predicates that describe processes that cannot easily be framed in terms of a state but that involve complex transitions through multiple hetereogeneous states:
Dependency graph for sentence: Kim was partying. Token partying is labeled SITUATION-DYN and has an edge labeled situee to token Kim.
Stacked with an Aspectual or Modal Frame
This often occurs with predicates that focus on aspect or made, leaving the precise nature of the relation between the two arguments underspecified.
Dependency graph for sentence: transition of the account to a new government. Token transition is labeled SITUATION-INIT and has an edge labeled situee to token account and an edge labeled situator to token government.
Dependency graph for sentence: they need three months. Token need is labeled SITUATION-NECESSITY and has an edge labeled situee to token they and an edge labeled situator to token months.
As a Default Frame
Use SITUATION if an entity is described as being in a state, but it is not
internal and there is not other frame that seems to fit
better.
Dependency graph for sentence: I was lost. Token lost is labeled SITUATION and has an edge labeled situee to token I.
ACCOMPANIMENT
Roles: accompanied, accompanier
accompanier accompanies accompanied, meaning that it occurs together with
it or participates equally in the same event.
Dependency graph for sentence: veggies with rice. Token veggies is labeled ENTITY and has an edge labeled ACCOMPANIER to token rice.
Dependency graph for sentence: The veggies come with rice. Token come is labeled ACCOMPANIMENT and has an edge labeled accompanied to token veggies and an edge labeled accompanier to token rice.
Dependency graph for sentence: Kim added rice to the veggies. Token added is labeled ACCOMPANIMENT-INIT and has an edge labeled CAUSER to token Kim and an edge labeled accompanier to token rice and an edge labeled accompanied to token veggies.
Dependency graph for sentence: Rolling thunder accompanies the rain. Token accompanies is labeled ACCOMPANIMENT and has an edge labeled accompanier to token thunder and an edge labeled accompanier to token rain.
Often, the accompanier denotes not the accompanying event but an entity participating in it, and must be metonymically understood as the event.
Dependency graph for sentence: Kim cycled to Rome with Sandy. Token cycled is labeled LOCATION-INIT and has an edge labeled has-location to token Kim and an edge labeled location to token Rome and an edge labeled ACCOMPANIER to token Sandy.
Dependency graph for sentence: Kim danced with Sandy. Token danced is labeled POSE-DYN and has an edge labeled has-pose to token Kim and an edge labeled ACCOMPANIER to token Sandy.
Dependency graph for sentence: Kim accompanied Sandy. Token accompanied is labeled ACCOMPANIMENT-DYN and has an edge labeled accompanier to token Kim and an edge labeled accompanied to token Sandy.
Dependency graph for sentence: Kim accompanied Sandy on the piano. Token accompanied is labeled ACCOMPANIMENT-DYN and has an edge labeled accompanier to token Kim and an edge labeled accompanied to token Sandy and an edge labeled MEANS to token piano.
COMBINATION
Roles: combined, combined-with
Special case of ACCOMPANIMENT where the two arguments are combined to form something new. Also use this for algebraic operations.
Dependency graph for sentence: Kim mixed the eggs with the flour. Token mixed is labeled COMBINATION-INIT and has an edge labeled CAUSER to token Kim and an edge labeled combined to token eggs and an edge labeled combined-with to token flour.
Dependency graph for sentence: Blend the vegetables into a smoothie. Token Blend is labeled COMBINATION-INIT and has an edge labeled combined to token vegetables and an edge labeled EFFECT to token smoothie.
Dependency graph for sentence: Twelve and three make fifteen. Token make is labeled COMBINATION and has an edge labeled combined to token Twelve and an edge labeled combined-with to token three and an edge labeled EFFECT to token fifteen.
COMPARISON
Roles: compared, reference
compared is characterized with respect to reference.
Dependency graph for sentence: It looked like this. Token looked is labeled COMPARISON and has an edge labeled compared to token It and an edge labeled reference to token this.
Dependency graph for sentence: Compared with Sandy , Kim is tall. Token Compared is labeled COMPARISON and has an edge labeled reference to token Sandy. Token tall is labeled PROPERTY and has an edge labeled SCENE to token Compared and an edge labeled has-property to token Kim.
Dependency graph for sentence: Sandy is short whereas Kim is tall. Token short is labeled PROPERTY and has an edge labeled has-property to token Sandy and an edge labeled REFERENCE to token tall. Token tall is labeled PROPERTY and has an edge labeled has-property to token Kim.
Dependency graph for sentence: They demonize the left while doing nothing about the right. Token demonize is labeled EVALUATION and has an edge labeled SENDER to token They and an edge labeled evaluee to token left. Token doing is labeled SITUATION-INIT and has an edge labeled CAUSER to token They and an edge labeled situator to token nothing and an edge labeled situee to token right.
Dependency graph for sentence: Kim exceeds Sandy in height. Token exceeds is labeled COMPARISON and has an edge labeled compared to token Kim and an edge labeled reference to token Sandy and an edge labeled REGARD to token height.
Dependency graph for sentence: The Polish restaurant compared favorably to the Spanish one. Token compared is labeled COMPARISON and has an edge labeled SCENE to token favorably and an edge labeled reference to token one. Token favorably is labeled PROPERTY and has an edge labeled has-property to token compared.
Dependency graph for sentence: Kim compared Coke to Pepsi. Token compared is labeled COMPARISON-MESSAGE-INIT and has an edge labeled EXPERIENCER to token Kim and an edge labeled compared to token Coke and an edge labeled reference to token Pepsi.
Dependency graph for sentence: I was more isolated than a shipwrecked sailor. Token more is labeled QUANTITY and has an edge labeled has-quantity to token isolated. Token isolated is labeled LOCATION-NEG and has an edge labeled has-location to token I and an edge labeled SCENE to token more and an edge labeled REFERENCE to token sailor.
Dependency graph for sentence: Kim is taller than Sandy. Token taller is labeled PROPERTY and has an edge labeled has-property to token Kim and an edge labeled REFERENCE to token Sandy.
Dependency graph for sentence: die unter allen Provinzen am drittstärksten bevölkerte. Token drittstärksten is labeled QUANTITY and has an edge labeled has-quantity to token bevölkerte. Token bevölkerte is labeled ENTITY and has an edge labeled REFERENCE to token Provinzen and an edge labeled SCENE to token drittstärksten.
Dependency graph for sentence: Kim outranks Sandy. Token outranks is labeled RANK and has an edge labeled has-rank to token Kim and an edge labeled REFERENCE to token Sandy.
Dependency graph for sentence: Kim outshines Sandy. Token outshines is labeled EXPRESSION and has an edge labeled sender to token Kim and an edge labeled REFERENCE to token Sandy.
Dependency graph for sentence: Sie versuchten, die Stimme zu übertönen. Token übertönen is labeled EXPRESSION and has an edge labeled sender to token Sie and an edge labeled REFERENCE to token Stimme.
reference need not be an entity similar to the compared, it can also be an
abstract constraint:
Dependency graph for sentence: The program conforms to the spec. Token conforms is labeled COMPARISON and has an edge labeled compared to token program and an edge labeled reference to token spec.
Dependency graph for sentence: Kim ran afoul of Fielding ’s constraints. Token ran is labeled META-INIT and has an edge labeled participant to token Kim. Token afoul is labeled COMPARISON-NEG and has an edge labeled compared to token Kim and an edge labeled reference to token constraints.
COMPETITION
Roles: competitor, cocompetitor
Denotes the outcome of a struggle or a competition. For the process of competition, stack an aspectual frame.
Dependency graph for sentence: Argentina is the current champion. Token champion is labeled COMPETITION and has an edge labeled competitor to token Argentina.
Dependency graph for sentence: Argentina beat France. Token beat is labeled COMPETITION-INIT and has an edge labeled competitor to token Argentina and an edge labeled cocompetitor to token France.
Dependency graph for sentence: Kim is fighting with Sandy. Token fighting is labeled COMPETITION-DYN and has an edge labeled competitor to token Kim and an edge labeled cocompetitor to token Sandy.
Dependency graph for sentence: The company is competing in a tough market. Token competing is labeled COMPETITION-DYN and has an edge labeled competitor to token company and an edge labeled SITUATOR to token market.
CONCESSION
Roles: asserted, conceded
Special case of COMPARISON, indicating a contrast between
something that’s the case (conceded) and something that seems to contradict it
but is the case anyway (asserted).
Dependency graph for sentence: Kim went out despite the rain. Token went is labeled LOCATION-INIT and has an edge labeled has-location to token Kim and an edge labeled location to token out and an edge labeled CONCEDED to token rain.
Dependency graph for sentence: It rained , but Kim went out. Token rained is labeled ENTITY and has an edge labeled NONCOMP to token It and an edge labeled ASSERTED to token went.
Dependency graph for sentence: Kim sent Sandy a message , but it never arrived. Token sent is labeled EXPRESSION and has an edge labeled sender to token Kim and an edge labeled EXPERIENCER to token Sandy and an edge labeled sent to token message and an edge labeled ASSERTED to token arrived.
Dependency graph for sentence: Kim went although Sandy had told them not to. Token went is labeled LOCATION-INIT and has an edge labeled has-location to token Kim and an edge labeled CONCEDED to token told.
Dependency graph for sentence: man wurde gegen seinen Willen in einen Verrückten verwandelt. Token Verrückten is labeled PROPERTY and has an edge labeled has-property to token man. Token verwandelt is labeled META-INIT and has an edge labeled participant to token man and an edge labeled CONCEDED to token Willen and an edge labeled scene to token Verrückten.
Dependency graph for sentence: We did it anyway. Token anyway is labeled CONCESSION and has an edge labeled asserted to token did.
IDENTITY
Roles: same, same-as
same is the same entity as same-as.
Dependency graph for sentence: Dividing by a fraction is the same as multiplying by its reciprocal. Token same is labeled IDENTITY and has an edge labeled same to token Dividing and an edge labeled same-as to token multiplying.
Dependency graph for sentence: Bruce Wayne is Batman. Token Batman is labeled ENTITY and has an edge labeled SAME to token Wayne.
Dependency graph for sentence: It was the drawing of the boa constrictor. Token drawing is labeled MESSAGE and has an edge labeled SAME to token It and an edge labeled content to token boa.
Dependency graph for sentence: That is why I stayed. Token why is labeled REASON and has an edge labeled has-reason to token stayed. Token stayed is labeled LOCATION-CONTINUATION and has an edge labeled SAME to token That and an edge labeled SCENE to token why and an edge labeled has-location to token I.
Dependency graph for sentence: the Desert of Sahara. Token Desert is labeled ENTITY and has an edge labeled SAME to token Sahara.
Dependency graph for sentence: the experiment of showing him my Drawing Number One. Token experiment is labeled ENTITY and has an edge labeled SAME to token showing.
Dependency graph for sentence: he broke into a peal of laughter. Token peal is labeled EXPRESSION and has an edge labeled sender to token he and an edge labeled SAME to token laughter.
Dependency graph for sentence: In answer , he repeated : Please , draw me a sheep !. Token repeated is labeled MESSAGE and has an edge labeled SAME to token answer and an edge labeled SENDER to token he and an edge labeled content to token draw.
The frame can be used to annotate (rare) syntactic links between two descriptions of the same event:
Dependency graph for sentence: And he continued his confidences : “ I did not know how to understand anything ! ”. Token continued is labeled META-CONTINUATION and has an edge labeled participant to token he and an edge labeled scene to token confidences and an edge labeled SAME to token know.
IDENTIFIER
Roles: identified, identifier
identified is identified by identifier. identifier can be a name, an ID,
a logo, or some other type of identifier.
Dependency graph for sentence: a book called True Stories from Nature. Token called is labeled IDENTIFIER and has an edge labeled identified to token book and an edge labeled identifier to token Stories.
Dependency graph for sentence: das Abzeichen der Jugendliga gegen Sexualität. Token Abzeichen is labeled IDENTIFIER and has an edge labeled identified to token Jugendliga.
INFLUENCE
Roles: affected, influence
influence is or exerts an influence over affected. affected can, among
other things, be a beneficiary or a maleficiary.
Dependency graph for sentence: Kim was saved from the dragon. Token saved is labeled INFLUENCE-PREVENTION and has an edge labeled affected to token Kim and an edge labeled influence to token dragon.
Dependency graph for sentence: when a mystery is too overpowering. Token overpowering is labeled INFLUENCE and has an edge labeled SCENE to token when and an edge labeled influence to token mystery and an edge labeled SCENE to token too.
Dependency graph for sentence: That does n't matter. Token matter is labeled INFLUENCE and has an edge labeled influence to token That and an edge labeled SCENE to token n't.
Dependency graph for sentence: They treat you like a child. Token treat is labeled INFLUENCE and has an edge labeled influence to token They and an edge labeled affected to token you and an edge labeled REFERENCE to token child.
Dependency graph for sentence: They leave you in peace from their questions. Token leave is labeled INFLUENCE-DEINIT and has an edge labeled CAUSER to token They and an edge labeled affected to token you and an edge labeled NONCOMP to token peace and an edge labeled influence to token questions.
Dependency graph for sentence: danger of the baobabs. Token danger is labeled INFLUENCE-POSSIBILITY and has an edge labeled influence to token baobabs.
Dependency graph for sentence: Kim did something nice for Sandy. Token did is labeled CAUSATION and has an edge labeled causer to token Kim and an edge labeled effect to token something and an edge labeled AFFECTED to token Sandy.
Dependency graph for sentence: Kim cooked a meal only to have Sandy spurn it. Token have is labeled META and has an edge labeled AFFECTED to token Kim and an edge labeled participant to token Sandy and an edge labeled scene to token spurn.
Dependency graph for sentence: 请 你 帮 我 点菜. Token 请 is labeled NORM and has an edge labeled norm-content to token 帮. Token 帮 is labeled META and has an edge labeled SCENE to token 请 and an edge labeled participant to token 你 and an edge labeled AFFECTED to token 我 and an edge labeled scene to token 点菜. Token 点菜 is labeled EXPRESSION-INIT and has an edge labeled sender to token 你.
CAUSATION
Roles: effect, causer
effect is brought about by causer.
Dependency graph for sentence: Kim broke the glass. Token broke is labeled INTERNAL-STATE-INIT and has an edge labeled CAUSER to token Kim and an edge labeled has-state to token glass.
Dependency graph for sentence: The knife cuts the bread. Token cuts is labeled INTERNAL-STATE-INIT and has an edge labeled CAUSER to token knife and an edge labeled has-state to token bread.
Dependency graph for sentence: Kim cuts the bread with a knife. Token cuts is labeled INTERNAL-STATE-INIT and has an edge labeled CAUSER to token Kim and an edge labeled has-state to token bread and an edge labeled MEANS to token knife.
Dependency graph for sentence: The war caused a famine. Token caused is labeled CAUSATION and has an edge labeled causer to token war and an edge labeled effect to token famine.
Dependency graph for sentence: There was a famine because of the war. Token was is labeled REALITY and has an edge labeled has-reality to token famine and an edge labeled CAUSER to token war.
Dependency graph for sentence: Der Wasserdruck stieg , wodurch der Brunnen überfloss. Token stieg is labeled INTERNAL-STATE-INIT and has an edge labeled has-state to token Wasserdruck and an edge labeled EFFECT to token überfloss. Token überfloss is labeled CONTAINMENT-DEINIT and has an edge labeled container to token Brunnen.
Dependency graph for sentence: Die Qualität ist der Motivation geschuldet. Token geschuldet is labeled CAUSATION and has an edge labeled effect to token Qualität and an edge labeled causer to token Motivation.
CREATION
Roles: creation, creator
Special case of CAUSATION that is used in connection with EXISTENCE-INIT
events, when the causer is the creator.
Dependency graph for sentence: I made my first drawing. Token made is labeled EXISTENCE-INIT and has an edge labeled CREATOR to token I and an edge labeled existent to token drawing. Token drawing is labeled CREATION and has an edge labeled creator to token I and an edge labeled SCENE to token first.
Dependency graph for sentence: my masterpiece. Token masterpiece is labeled CREATION and has an edge labeled creator to token my.
EXPRESSION
Roles: sent, sender
sender originates a message, sent, that can be perceived.
Dependency graph for sentence: Kim yelped. Token yelped is labeled EXPRESSION-INIT and has an edge labeled sender to token Kim.
Dependency graph for sentence: Kim and Sandy conversed. Token conversed is labeled EXPRESSION-INIT and has an edge labeled sender to token Kim and an edge labeled sender to token Sandy.
Dependency graph for sentence: Kim conversed with Sandy. Token conversed is labeled EXPRESSION-INIT and has an edge labeled sender to token Kim and an edge labeled ACCOMPANIER to token Sandy.
Dependency graph for sentence: Kim curtseyed to the Queen. Token curtseyed is labeled EXPRESSION-INIT and has an edge labeled sender to token Kim and an edge labeled EXPERIENCER to token Queen.
Dependency graph for sentence: Kim shook their head. Token shook is labeled EXPRESSION-INIT and has an edge labeled sender to token Kim and an edge labeled NONCOMP to token head.
PERFORMANCE
Roles: work, performer
performer performs a work (of art).
Dependency graph for sentence: Kim played a little tune on their tuba. Token played is labeled PERFORMANCE-INIT and has an edge labeled performer to token Kim and an edge labeled work to token tune and an edge labeled MEANS to token tuba.
Dependency graph for sentence: They performed the play. Token performed is labeled PERFORMANCE-INIT and has an edge labeled performer to token They and an edge labeled work to token play.
Dependency graph for sentence: Kim sang a song. Token sang is labeled PERFORMANCE-INIT and has an edge labeled performer to token Kim and an edge labeled work to token song.
MEANS
Roles: end, means
means is an intermediary causer of or is destined to serve an end (i.e., a
purpose).
Dependency graph for sentence: Kim cut the cake with a knife. Token cut is labeled INTERNAL-STATE-INIT and has an edge labeled CAUSER to token Kim and an edge labeled has-state to token cake and an edge labeled MEANS to token knife.
Dependency graph for sentence: Kim painted the room by exploding a paint bomb. Token painted is labeled CONTACT-INIT and has an edge labeled CAUSER to token Kim and an edge labeled surface to token room and an edge labeled MEANS to token exploding.
Dependency graph for sentence: Kim used a pen to get the lid off. Token used is labeled MEANS and has an edge labeled CAUSER to token Kim and an edge labeled means to token pen and an edge labeled end to token get.
Dependency graph for sentence: You used me !. Token used is labeled MEANS and has an edge labeled CAUSER to token You and an edge labeled means to token me.
Dependency graph for sentence: Kim went to town to buy food. Token went is labeled LOCATION-INIT and has an edge labeled has-location to token Kim and an edge labeled location to token town and an edge labeled END to token buy.
ASSET
Roles: has-asset, asset
has-asset is an exchange or wager or a good or service subject to an exchange
or wager, and asset is given or offered in return.
Dependency graph for sentence: a house that cost $ 20,000. Token cost is labeled ASSET and has an edge labeled has-asset to token house and an edge labeled asset to token $.
Dependency graph for sentence: Kim bought the house for a million dollars. Token bought is labeled POSSESSION-INIT and has an edge labeled possessor to token Kim and an edge labeled possessum to token house and an edge labeled ASSET to token dollars.
Dependency graph for sentence: Kim offered Sandy a million dollars for the house. Token offered is labeled POSSESSION-INIT and has an edge labeled possessor-DEINIT to token Kim and an edge labeled possessor to token Sandy and an edge labeled possessum to token dollars and an edge labeled ASSET to token house.
Dependency graph for sentence: I bet you 30 bucks to an apple he will win. Token bet is labeled MESSAGE-INIT and has an edge labeled SENDER to token I and an edge labeled ASSET to token bucks and an edge labeled ASSET to token apple and an edge labeled content to token win.
MEDIUM
Roles: transmission, medium
medium is used to effect a transmission.
Dependency graph for sentence: I saw a picture in a book. Token saw is labeled MESSAGE and has an edge labeled EXPERIENCER to token I and an edge labeled content to token picture and an edge labeled MEDIUM to token book.
Dependency graph for sentence: In the book it said boas swallow their prey whole. Token said is labeled MESSAGE and has an edge labeled MEDIUM to token book and an edge labeled NONCOMP to token it and an edge labeled content to token swallow.
Dependency graph for sentence: Everything was revealed to me from words. Token revealed is labeled MESSAGE-INIT and has an edge labeled content to token Everything and an edge labeled EXPERIENCER to token me and an edge labeled MEDIUM to token words.
Dependency graph for sentence: seeing them through the telescope. Token seeing is labeled MESSAGE and has an edge labeled content to token them and an edge labeled MEDIUM to token telescope.
Dependency graph for sentence: I describe him here. Token here is labeled MEDIUM and has an edge labeled transmission to token describe.
Dependency graph for sentence: no other drawing in this book. Token drawing is labeled ENTITY and has an edge labeled MEDIUM to token book.
Dependency graph for sentence: the book contains many drawings. Token contains is labeled MEDIUM and has an edge labeled medium to token book and an edge labeled transmission to token drawings.
REACTION
Roles: reaction, trigger
trigger triggers a reaction in some other, more direct causer.
Dependency graph for sentence: Kim reacted to the allegations with a denial. Token reacted is labeled META-INIT and has an edge labeled participant to token Kim and an edge labeled TRIGGER to token allegations and an edge labeled scene to token denial. Token denial is labeled EXPRESSION-INIT and has an edge labeled sender to token Kim.
Dependency graph for sentence: He found nothing to say in answer to my question. Token say is labeled MESSAGE-INIT and has an edge labeled SENDER to token He and an edge labeled content to token nothing and an edge labeled SCENE to token answer. Token answer is labeled REACTION and has an edge labeled reaction to token say and an edge labeled trigger to token question.
CONDITION
Roles: has-condition, condition
condition is presented as a (necessary or sufficient) condition for
has-condition.
Dependency graph for sentence: I will join the club if they ask me. Token join is labeled BOND-INIT and has an edge labeled tied to token I and an edge labeled tied-to to token club and an edge labeled CONDITION to token ask.
Dependency graph for sentence: The start date is contingent on their approval. Token contingent is labeled CONDITION and has an edge labeled has-condition to token date and an edge labeled condition to token approval.
Dependency graph for sentence: Eine Aussöhnung bedingt eine Entschuldigung. Token bedingt is labeled CONDITION and has an edge labeled has-condition to token Aussöhnung and an edge labeled condition to token Entschuldigung.
EXCEPTION
Roles: has-exception, exception
exception is an exception to has-exception.
Dependency graph for sentence: Except for Kim , everybody joined. Token joined is labeled BOND-INIT and has an edge labeled EXCEPTION to token Kim and an edge labeled tied to token everybody.
Dependency graph for sentence: I have never made any pictures except those of the boa constrictor. Token made is labeled EXISTENCE-INIT and has an edge labeled CREATOR to token I and an edge labeled SCENE to token never and an edge labeled existent to token pictures and an edge labeled EXCEPTION to token boa.
LIMIT
Roles: limited, limit
The denotation of the limited dependent is restricted to the denotation of
the limit dependent. With words like only, only one role is usually
realized as a syntactic dependency. In the following examples, we nevertheless
add the other role for clarity.
Dependency graph for sentence: Our access is restricted to what we need to know. Token restricted is labeled LIMIT and has an edge labeled limited to token access and an edge labeled limit to token know.
Dependency graph for sentence: This is only his box. Token only is labeled LIMIT and has an edge labeled limited to token This and an edge labeled limit to token box.
Dependency graph for sentence: It is not given a name , only a number. Token only is labeled LIMIT and has an edge labeled limited to token given and an edge labeled limit to token number.
Dependency graph for sentence: It has been seen only once. Token only is labeled LIMIT and has an edge labeled limited to token seen and an edge labeled limit to token once.
Dependency graph for sentence: Only from these figures do they think they have learned anything. Token Only is labeled LIMIT and has an edge labeled limit to token figures and an edge labeled limited to token learned.
Dependency graph for sentence: It is only a sprout. Token only is labeled LIMIT and has an edge labeled limited to token It and an edge labeled limit to token sprout.
Dependency graph for sentence: you had found your only entertainment in the quiet pleasure of looking at the sunset. Token only is labeled LIMIT and has an edge labeled limited to token entertainment and an edge labeled limit to token pleasure.
Dependency graph for sentence: moving your chair is all you need to do. Token moving is labeled LOCATION-INIT and has an edge labeled has-location to token chair and an edge labeled CAUSER to token you. Token all is labeled LIMIT and has an edge labeled limit to token moving and an edge labeled limited to token need. Token need is labeled META-NECESSITY and has an edge labeled participant to token you and an edge labeled scene to token do. Token do is labeled META-INIT and has an edge labeled scene to token moving and an edge labeled participant to token you.
Dependency graph for sentence: all you need to do is move your chair. Token all is labeled LIMIT and has an edge labeled limited to token need and an edge labeled limit to token move. Token need is labeled META-NECESSITY and has an edge labeled participant to token you and an edge labeled scene to token do. Token do is labeled META-INIT and has an edge labeled participant to token you and an edge labeled scene to token move. Token move is labeled LOCATION-INIT and has an edge labeled CAUSER to token you and an edge labeled SCENE to token need and an edge labeled has-location to token chair.
PROPORTION
Roles: numerator, denominator
Used to indicate proportional amounts.
Dependency graph for sentence: It costs 1 euro per scoop. Token costs is labeled ASSET and has an edge labeled has-asset to token It and an edge labeled asset to token euro and an edge labeled DENOMINATOR to token scoop.
EXPERIENCE
Roles: experiencer, experienced
Special case of INFLUENCE where experienced is a
MESSAGE and experiencer is (potentially) affected by it
through sensory or mental perception. Addressees of messages can be labeled
experiencer even if we don’t know if they ever perceive the message.
Dependency graph for sentence: I saw a magnificent picture. Token saw is labeled MESSAGE and has an edge labeled EXPERIENCER to token I and an edge labeled content to token picture.
Dependency graph for sentence: I pondered over the adventure of the jungle. Token pondered is labeled MESSAGE-INIT and has an edge labeled EXPERIENCER to token I and an edge labeled content to token adventure.
Dependency graph for sentence: Kim talked to Sandy. Token talked is labeled EXPRESSION-INIT and has an edge labeled sender to token Kim and an edge labeled EXPERIENCER to token Sandy.
Dependency graph for sentence: Das ist mir zu dunkel. Token dunkel is labeled PROPERTY and has an edge labeled has-property to token Das and an edge labeled EXPERIENCER to token mir and an edge labeled SCENE to token zu.
Dependency graph for sentence: Das hat mir gerade noch gefehlt. Token gefehlt is labeled EVALUATION and has an edge labeled evaluee to token Das and an edge labeled EXPERIENCER to token mir and an edge labeled NONCOMP to token gerade and an edge labeled NONCOMP to token noch.
REASON
Roles: has-reason, reason
reason is a reason for has-reason. Useful if the reason is too vague or
indirect or epistemic to call it a cause.
Dependency graph for sentence: She must be a gardener , because he had seen her with a spade. Token gardener is labeled ENTITY and has an edge labeled INSTANCE to token She and an edge labeled REASON to token seen.
Dependency graph for sentence: Why should any one be frightened by a hat ?. Token Why is labeled REASON and has an edge labeled has-reason to token frightened.
Dependency graph for sentence: Since the grown-ups were not able to understand it , I made another drawing. Token made is labeled EXISTENCE-INIT and has an edge labeled REASON to token able and an edge labeled CREATOR to token I and an edge labeled existent to token drawing.
Dependency graph for sentence: So then I chose another profession. Token So is labeled REASON and has an edge labeled has-reason to token chose.
INTERNAL-STATE
Roles: has-state, state
The entity with the has-state role is in a state that is construed as
internal to it, rather than consisting in its relation to some other entity.
Typical examples include things such as being open or closed, whole or broken,
asleep or awake.
Dependency graph for sentence: They eat their prey whole without chewing it. Token whole is labeled INTERNAL-STATE and has an edge labeled has-state to token prey. Token chewing is labeled INTERNAL-STATE-INIT and has an edge labeled CAUSER to token They and an edge labeled has-state to token it.
Dependency graph for sentence: They sleep through the six months that they need for digestion. Token sleep is labeled INTERNAL-STATE and has an edge labeled has-state to token They.
Dependency graph for sentence: a boa constrictor digesting an elephant. Token digesting is labeled INTERNAL-STATE-INIT and has an edge labeled CAUSER to token boa and an edge labeled has-state to token elephant.
Dependency graph for sentence: that hasn't much improved my opinion of them. Token improved is labeled INTERNAL-STATE-INIT and has an edge labeled CAUSER to token that and an edge labeled SCENE to token much and an edge labeled has-state to token opinion.
Dependency graph for sentence: Something was broken in my engine. Token broken is labeled INTERNAL-STATE and has an edge labeled has-state to token Something and an edge labeled REGARD to token engine.
Dependency graph for sentence: I was awakened by a little voice. Token awakened is labeled INTERNAL-STATE-INIT and has an edge labeled has-state to token I and an edge labeled CAUSER to token voice.
Dependency graph for sentence: Kim opened the window. Token opened is labeled INTERNAL-STATE-INIT and has an edge labeled CAUSER to token Kim and an edge labeled has-state to token window.
Because there is no “other entity”, the second role of this frame and all
its subframes is rarely used. It denotes the state itself, which is normally
fully expressed by the predicate and does not need another argument. If the
state was fully expressed by another argument, the predicate should have META
as its base frame. However, there are some cases (rare in English) where a
predicate and an argument jointly express a state, illustrated below with the
QUANTITY frame. In such cases, INTERNAL-STATE and its
subframes can appear with a second core argument.
Dependency graph for sentence: They number in the thousands. Token number is labeled QUANTITY and has an edge labeled has-quantity to token They and an edge labeled quantity to token thousands.
POSE
Roles: has-pose, pose
Special case of INTERNAL-STATE desribing someone or something’s internal spatial configuration, e.g., body pose or posture.
Dependency graph for sentence: I jumped to my feet. Token jumped is labeled POSE-INIT and has an edge labeled has-pose to token I and an edge labeled NONCOMP to token feet. Token feet is labeled POSE-INIT and has an edge labeled has-pose to token my.
Dependency graph for sentence: a small person who stood there. Token stood is labeled POSE and has an edge labeled has-pose to token person and an edge labeled has-pose to token who and an edge labeled SCENE to token there.
PROPERTY
Roles: has-property, property
A special case of INTERNAL-STATE where the state is construed as stable, i.e.,
a concept that describes something that persists over time, and is construed to be a relatively inherent characteristic of the object over its lifetime. Example: being smart or being heavy (of a stone slab) are stable states. The stability of states is a matter of construal; a state construed as stable may change – for example, a tall tree whose top is broken off.
Dependency graph for sentence: a magnificent picture. Token magnificent is labeled PROPERTY and has an edge labeled has-property to token picture.
Dependency graph for sentence: True Stories from Nature. Token True is labeled PROPERTY and has an edge labeled has-property to token Stories.
Dependency graph for sentence: I pondered deeply. Token deeply is labeled PROPERTY and has an edge labeled has-property to token pondered.
Dependency graph for sentence: a colored pencil. Token colored is labeled PROPERTY and has an edge labeled has-property to token pencil.
Dependency graph for sentence: see clearly. Token clearly is labeled PROPERTY and has an edge labeled has-property to token see.
Dependency graph for sentence: such knowledge is very valuable. Token valuable is labeled PROPERTY and has an edge labeled has-property to token knowledge.
Dependency graph for sentence: primeval forests. Token primeval is labeled PROPERTY and has an edge labeled has-property to token forests.
Dependency graph for sentence: I would bring myself down to his level. Token bring is labeled META-INIT and has an edge labeled participant to token myself and an edge labeled scene to token down. Token down is labeled PROPERTY-INIT and has an edge labeled has-property to token myself and an edge labeled EFFECT to token level. Token level is labeled PROPERTY and has an edge labeled has-property to token myself and an edge labeled has-property to token his.
Dependency graph for sentence: an odd little voice. Token odd is labeled PROPERTY and has an edge labeled has-property to token voice. Token little is labeled PROPERTY and has an edge labeled has-property to token voice.
Dependency graph for sentence: this sudden apparition. Token sudden is labeled PROPERTY and has an edge labeled has-property to token apparition.
Dependency graph for sentence: Absurd as it might seem , I took out a fountain pen. Token Absurd is labeled PROPERTY and has an edge labeled REFERENCE to token seem and an edge labeled has-property to token took. Token took is labeled CONTAINMENT-DEINIT and has an edge labeled SCENE to token Absurd and an edge labeled CAUSER to token I and an edge labeled contained to token pen.
Dependency graph for sentence: That is exactly the way I wanted it. Token way is labeled PROPERTY and has an edge labeled has-property to token That and an edge labeled SCENE to token exactly and an edge labeled SCENE to token wanted.
Dependency graph for sentence: How much does he weigh ?. Token weigh is labeled PROPERTY and has an edge labeled SCENE to token much and an edge labeled has-property to token he.
Dependency graph for sentence: the little prince 's height. Token height is labeled PROPERTY and has an edge labeled has-property to token prince.
Dependency graph for sentence: the color of his costume. Token color is labeled PROPERTY and has an edge labeled has-property to token costume.
QUANTITY
Roles: has-quantity, quantity
quantity is the quantity, degree, or extent of has-quantity.
Dependency graph for sentence: three burgers. Token three is labeled QUANTITY and has an edge labeled has-quantity to token burgers.
Dependency graph for sentence: a liter of coke. Token liter is labeled QUANTITY and has an edge labeled has-quantity to token coke.
Dependency graph for sentence: much improved. Token much is labeled QUANTITY and has an edge labeled has-quantity to token improved.
Dependency graph for sentence: Sie sang so schön , dass wir weinten. Token so is labeled QUANTITY and has an edge labeled has-quantity to token schön.
Dependency graph for sentence: They number in the thousands. Token number is labeled QUANTITY and has an edge labeled has-quantity to token They and an edge labeled quantity to token thousands.
For counts or lengths of eventualities, use TIME instead:
Dependency graph for sentence: Kim sneezed twice. Token twice is labeled TIME and has an edge labeled has-time to token sneezed.
Dependency graph for sentence: Kim laughed for hours. Token laughed is labeled EXPRESSION-INIT and has an edge labeled TIME to token hours.
Dependency graph for sentence: a moment of complete silence. Token moment is labeled TIME and has an edge labeled has-time to token silence.
RANK
Roles: has-rank, rank
rank indicates the order that has-rank has in some sequence.
Dependency graph for sentence: Chapter 1. Token 1 is labeled RANK and has an edge labeled has-rank to token Chapter.
Dependency graph for sentence: my first drawing. Token first is labeled RANK and has an edge labeled has-rank to token drawing.
Dependency graph for sentence: Kim ranked second among all players. Token ranked is labeled RANK and has an edge labeled has-rank to token Kim and an edge labeled rank to token second and an edge labeled REFERENCE to token players. Token second is labeled RANK and has an edge labeled has-rank to token Kim.
REALITY
Roles: has-reality, reality
Property of predicate occurrences, describing the relationship between the predicate used and the eventuality it describes in terms of how true or certain (vs. false or speculative) it is.
Dependency graph for sentence: Passt das eh ?. Token eh is labeled REALITY and has an edge labeled has-reality to token Passt.
Dependency graph for sentence: Kim probably knows that. Token probably is labeled REALITY and has an edge labeled has-reality to token knows.
Dependency graph for sentence: That 's really great. Token really is labeled REALITY and has an edge labeled has-reality to token great.
Dependency graph for sentence: It is true that geography has been very useful to me. Token true is labeled REALITY and has an edge labeled has-reality to token useful.
Dependency graph for sentence: it is to make sure that I shall not forget him. Token sure is labeled REALITY and has an edge labeled has-reality to token forget.
Dependency graph for sentence: That is strictly correct. Token correct is labeled REALITY and has an edge labeled has-reality to token That and an edge labeled SCENE to token strictly.
Dependency graph for sentence: Indeed , there were good plants and bad plants. Token Indeed is labeled REALITY and has an edge labeled has-reality to token were.
EXISTENCE
Roles: existent, existence
Used to indicate that something exists. Use EXISTENCE only for
non-eventualities like objects. For eventualities, use REALITY
or a bare aspectual frame instead.
Dependency graph for sentence: I exist. Token exist is labeled EXISTENCE and has an edge labeled existent to token I.
Dependency graph for sentence: There is a hill. Token is is labeled EXISTENCE and has an edge labeled NONCOMP to token There and an edge labeled existent to token hill.
Dependency graph for sentence: I made a sculpture. Token made is labeled EXISTENCE-INIT and has an edge labeled CREATOR to token I and an edge labeled existent to token sculpture.
Dependency graph for sentence: There is a famine. Token is is labeled REALITY and has an edge labeled has-reality to token famine.
Dependency graph for sentence: The question was born from silence. Token born is labeled INIT and has an edge labeled initiated to token question and an edge labeled CAUSER to token silence.
LITERALITY
Roles: has-literality, literality
Property of predicate occurrences, describing the relationship between the predicate used and the eventuality it describes in terms of how literal (vs. figurative) it is.
Dependency graph for sentence: There are literally thousands. Token literally is labeled LITERALITY and has an edge labeled has-literality to token thousands.
Dependency graph for sentence: It 's the proverbial chicken and egg situation. Token proverbial is labeled LITERALITY and has an edge labeled has-literality to token situation.
PRECISION
Roles: has-precision, precision
Property of predicate occurrences, describing the relationship between the predicate used and the eventuality it describes in terms of how precise (vs. vague) it is.
Dependency graph for sentence: Just so. Token Just is labeled PRECISION and has an edge labeled has-precision to token so.
Dependency graph for sentence: exactly how all this is. Token exactly is labeled PRECISION and has an edge labeled has-precision to token how.
Dependency graph for sentence: at this very moment. Token very is labeled PRECISION and has an edge labeled has-precision to token moment.
Dependency graph for sentence: That is exactly the way I wanted it !. Token exactly is labeled PRECISION and has an edge labeled has-precision to token way.
Dependency graph for sentence: It was rejected , just like the others. Token just is labeled PRECISION and has an edge labeled has-precision to token others.
Dependency graph for sentence: there is a certain red-faced gentleman. Token certain is labeled PRECISION and has an edge labeled has-precision to token gentleman.
NECESSITY
Roles: necessary, necessity
Used to indicate that something is necessary, either in an epistemic or deontic sense.
Dependency graph for sentence: That is necessary. Token necessary is labeled NECESSITY and has an edge labeled necessary to token That.
Dependency graph for sentence: the necessity of breathing. Token necessity is labeled NECESSITY and has an edge labeled necessary to token breathing.
Dependency graph for sentence: Kim has to come. Token has is labeled META-NECESSITY and has an edge labeled participant to token Kim and an edge labeled scene to token come.
Dependency graph for sentence: Kim needs time. Token needs is labeled SITUATION-NECESSITY and has an edge labeled situee to token Kim and an edge labeled situator to token time.
Dependency graph for sentence: Kim owes Sandy money. Token owes is labeled POSSESSION-DEINIT-NECESSITY and has an edge labeled possessor to token Kim and an edge labeled possessor-INIT to token Sandy and an edge labeled possessum to token money.
NEG
Roles: negated, negation
This frame denotes negation. It can be used by itself or stacked onto META or
other frames.
Dependency graph for sentence: They are not able to move. Token not is labeled NEG and has an edge labeled negated to token able.
Dependency graph for sentence: absence of evidence. Token absence is labeled EXISTENCE-NEG and has an edge labeled existent to token evidence.
Dependency graph for sentence: They never understand. Token never is labeled TIME-NEG and has an edge labeled has-time to token understand.
Dependency graph for sentence: But seeds are invisible. Token invisible is labeled MESSAGE-POSSIBILITY-NEG and has an edge labeled content to token seeds.
POSSIBILITY
Roles: possible, possibility
Used to indicate that something is possible, or someone is capable of something.
Dependency graph for sentence: That is possible. Token possible is labeled POSSIBILITY and has an edge labeled possible to token That.
Dependency graph for sentence: That is impossible. Token impossible is labeled POSSIBILITY-NEG and has an edge labeled possible to token That.
Dependency graph for sentence: Kim is able to come. Token able is labeled META-POSSIBILITY and has an edge labeled participant to token Kim and an edge labeled scene to token come.
Dependency graph for sentence: I learned to fly a plane. Token learned is labeled META-POSSIBILITY-INIT and has an edge labeled participant to token I and an edge labeled scene to token plane.
LOCATION
Roles: has-location, location
Describes has-location as located with respect to location.
Dependency graph for sentence: Kim lives in Boston. Token lives is labeled LOCATION-HABIT and has an edge labeled has-location to token Kim and an edge labeled location to token Boston.
Dependency graph for sentence: Kim went from the living room through the door into the kitchen. Token went is labeled LOCATION-INIT and has an edge labeled has-location to token Kim and an edge labeled location-INIT to token room and an edge labeled location-TRANSIT to token door and an edge labeled location to token kitchen.
Dependency graph for sentence: Kim placed the hat on the table. Token placed is labeled LOCATION-INIT and has an edge labeled CAUSER to token Kim and an edge labeled has-location to token hat and an edge labeled location to token table.
Dependency graph for sentence: Kim ist oben. Token oben is labeled LOCATION and has an edge labeled has-location to token Kim.
Dependency graph for sentence: Kim is running. Token running is labeled LOCATION-DYN and has an edge labeled has-location to token Kim.
Dependency graph for sentence: Kim is running along the river. Token running is labeled LOCATION-TRANSIT and has an edge labeled has-location to token Kim and an edge labeled location to token river.
Dependency graph for sentence: I learned to pilot airplanes. Token pilot is labeled LOCATION-DYN and has an edge labeled CAUSER to token I and an edge labeled has-location to token airplanes.
Dependency graph for sentence: Kim is dancing around the room with Sandy. Token dancing is labeled LOCATION-TRANSIT and has an edge labeled has-location to token Kim and an edge labeled location to token room and an edge labeled ACCOMPANIER to token Sandy.
Dependency graph for sentence: Kim is an avid unicyclist. Token unicyclist is labeled LOCATION-DYN and has an edge labeled has-location to token Kim.
CONTACT
Roles: ornament, surface
Special case of LOCATION where ornament is on the surface
of something.
Dependency graph for sentence: Kim hit Sandy. Token hit is labeled CONTACT-INIT and has an edge labeled CAUSER to token Kim and an edge labeled surface to token Sandy.
Dependency graph for sentence: Kim hit Sandy with a stick. Token hit is labeled CONTACT-INIT and has an edge labeled CAUSER to token Kim and an edge labeled surface to token Sandy and an edge labeled ornament to token stick.
Dependency graph for sentence: The stick hit Sandy. Token hit is labeled CONTACT-INIT and has an edge labeled ornament to token stick and an edge labeled surface to token Sandy.
Dependency graph for sentence: Kim kicked Sandy. Token kicked is labeled CONTACT-INIT and has an edge labeled CAUSER to token Kim and an edge labeled surface to token Sandy.
Dependency graph for sentence: Kim hit Sandy on the head with a pool noodle. Token hit is labeled CONTACT-INIT and has an edge labeled CAUSER to token Kim and an edge labeled surface to token Sandy and an edge labeled REGARD to token head and an edge labeled ornament to token noodle. Token head is labeled ENTITY and has an edge labeled WHOLE to token Sandy.
Dependency graph for sentence: Kim decorated the balcony with fairy lights. Token decorated is labeled CONTACT-INIT and has an edge labeled CAUSER to token Kim and an edge labeled surface to token balcony and an edge labeled ornament to token lights.
Dependency graph for sentence: Kim splashed Sandy with water. Token splashed is labeled CONTACT-INIT and has an edge labeled CAUSER to token Kim and an edge labeled surface to token Sandy and an edge labeled ornament to token water.
Dependency graph for sentence: Kim washed the dirt off Sandy. Token washed is labeled CONTACT-DEINIT and has an edge labeled CAUSER to token Kim and an edge labeled ornament to token dirt and an edge labeled surface to token Sandy.
Dependency graph for sentence: Kim washed Sandy. Token washed is labeled CONTACT-DEINIT and has an edge labeled CAUSER to token Kim and an edge labeled surface to token Sandy.
CONTAINMENT
Roles: contained, container
Describes contained as contained in container. Also used for events of
ingestion and excretion.
Dependency graph for sentence: a hat in a box. Token hat is labeled ENTITY and has an edge labeled CONTAINER to token box.
Dependency graph for sentence: Kim threw up the pretzel. Token threw is labeled CONTAINMENT-DEINIT and has an edge labeled container to token Kim and an edge labeled contained to token pretzel.
Dependency graph for sentence: Kim ate an apple. Token ate is labeled CONTAINMENT-INIT and has an edge labeled container to token Kim and an edge labeled contained to token apple.
Dependency graph for sentence: Kim sneezed. Token sneezed is labeled CONTAINMENT-DEINIT and has an edge labeled container to token Kim.
ORIENTATION
Roles: oriented, landmark
oriented is oriented in space with respect to landmark.
Dependency graph for sentence: Die Nadel zeigte nach Norden. Token zeigte is labeled ORIENTATION and has an edge labeled oriented to token Nadel and an edge labeled landmark to token Norden.
Dependency graph for sentence: Er wandte dem Televisor den Rücken zu. Token wandte is labeled ORIENTATION and has an edge labeled oriented to token Er and an edge labeled landmark to token Televisor and an edge labeled REGARD to token Rücken. Token Rücken is labeled ENTITY and has an edge labeled WHOLE to token Er.
PURSUIT
Roles: pursuer, pursued
Denotes a state where pursuer has arrived in a location by following
pursued there. To denote the process of pursuing, stack an aspectual frame.
Dependency graph for sentence: The police followed Winston around. Token followed is labeled PURSUIT-DYN and has an edge labeled pursuer to token police and an edge labeled pursued to token Winston.
Dependency graph for sentence: Kim followed Sandy into the attic. Token followed is labeled PURSUIT-INIT and has an edge labeled pursuer to token Kim and an edge labeled pursued to token Sandy and an edge labeled LOCATION-INIT to token attic.
WRAPPING-WEARING
Roles: worn, wearer
Used for events of wrapping and wearing, where the borders between containment and contact are fluid.
Dependency graph for sentence: Kim is wearing a shirt. Token wearing is labeled WRAPPING-WEARING and has an edge labeled wearer to token Kim and an edge labeled worn to token shirt.
Dependency graph for sentence: Kim is wearing glasses. Token wearing is labeled WRAPPING-WEARING and has an edge labeled wearer to token Kim and an edge labeled worn to token glasses.
Dependency graph for sentence: The shroud wraps the scepter. Token wraps is labeled WRAPPING-WEARING and has an edge labeled worn to token shroud and an edge labeled wearer to token scepter.
Dependency graph for sentence: Kim put on a sweater. Token put is labeled WRAPPING-WEARING-INIT and has an edge labeled wearer to token Kim and an edge labeled worn to token sweater.
Dependency graph for sentence: Kim took off their glasses. Token took is labeled WRAPPING-WEARING-DEINIT and has an edge labeled wearer to token Kim and an edge labeled worn to token glasses.
MESSAGE
Roles: content, message2
message2 is a message about content or whose content is content. It may
exist in expressed, perceived, and/or recorded form. Combine with
SENDER, EXPERIENCER, and/or
MEDIUM as needed.
Dependency graph for sentence: Kim 's speech about fish. Token speech is labeled MESSAGE and has an edge labeled SENDER to token Kim and an edge labeled content to token fish.
Dependency graph for sentence: Kim 's knowledge of fish. Token knowledge is labeled MESSAGE and has an edge labeled EXPERIENCER to token Kim and an edge labeled content to token fish.
Dependency graph for sentence: a picture of a boa constrictor in a book. Token picture is labeled MESSAGE and has an edge labeled content to token boa and an edge labeled MEDIUM to token book.
Message Initiation and Deinitiation
When a message is created through expression or perception (including
observation), use INIT:
Dependency graph for sentence: Kim talked about fish. Token talked is labeled MESSAGE-INIT and has an edge labeled SENDER to token Kim and an edge labeled content to token fish.
Dependency graph for sentence: Kim drew a fish. Token drew is labeled MESSAGE-INIT and has an edge labeled SENDER to token Kim and an edge labeled content to token fish.
Dependency graph for sentence: Kim watched the fish. Token watched is labeled MESSAGE-INIT and has an edge labeled EXPERIENCER to token Kim and an edge labeled content to token fish.
Dependency graph for sentence: The concert was recorded on tape. Token recorded is labeled MESSAGE-INIT and has an edge labeled content to token concert and an edge labeled MEDIUM to token tape.
Predicates that denote the deinititation of perception use MESSAGE-DEINIT:
Dependency graph for sentence: Kim forgot everything they knew. Token forgot is labeled MESSAGE-DEINIT and has an edge labeled EXPERIENCER to token Kim and an edge labeled content to token everything.
Message Predicates with Control Constructions
Some predicates express their content through a control construction, in which case combine with META:
Dependency graph for sentence: Kim called Sandy a liar. Token called is labeled META-MESSAGE-INIT and has an edge labeled SENDER to token Kim and an edge labeled participant to token Sandy and an edge labeled scene to token liar. Token liar is labeled EXPRESSION-HABIT and has an edge labeled sender to token Sandy.
Dependency graph for sentence: Kim watched Sandy swim. Token watched is labeled META-MESSAGE-INIT and has an edge labeled EXPERIENCER to token Kim and an edge labeled participant to token Sandy and an edge labeled scene to token swim. Token swim is labeled LOCATION-DYN and has an edge labeled has-location to token Sandy.
content is used for reported speech, direct or indirect:
Dependency graph for sentence: Kim said : it ’s fine. Token said is labeled MESSAGE-INIT and has an edge labeled SENDER to token Kim and an edge labeled content to token fine.
Dependency graph for sentence: Kim said it was fine. Token said is labeled MESSAGE-INIT and has an edge labeled SENDER to token Kim and an edge labeled content to token fine.
The message2 Role
The message2 role should only be used in those cases where the predicate
refers to a message by itself, and so does the argument. For example:
Dependency graph for sentence: He asked me many questions. Token asked is labeled MESSAGE-INIT and has an edge labeled SENDER to token He and an edge labeled EXPERIENCER to token me and an edge labeled message2 to token questions.
Dependency graph for sentence: Kim drew a picture. Token drew is labeled MESSAGE-INIT and has an edge labeled SENDER to token Kim and an edge labeled message2 to token picture.
Dependency graph for sentence: Kim SENDER sent Sandy a message. Token sent is labeled MESSAGE-INIT and has an edge labeled EXPERIENCER to token Sandy and an edge labeled message2 to token message.
Dependency graph for sentence: Kim SENDER told Sandy a story. Token told is labeled MESSAGE-INIT and has an edge labeled EXPERIENCER to token Sandy and an edge labeled message2 to token story.
By contrast, for a light predicate like gave, use META:
Dependency graph for sentence: Kim gave a speech. Token gave is labeled META-INIT and has an edge labeled participant to token Kim and an edge labeled scene to token speech. Token speech is labeled EXPRESSION and has an edge labeled sender to token Kim.
And with predicates of perception, use content for the message, because it
existed before the perception:
Dependency graph for sentence: He never heard the questions I asked him. Token heard is labeled MESSAGE-INIT and has an edge labeled EXPERIENCER to token He and an edge labeled SCENE to token never and an edge labeled content to token questions.
Dependency graph for sentence: I wanted to learn something about him. Token learn is labeled MESSAGE-INIT and has an edge labeled EXPERIENCER to token I and an edge labeled content to token something.
Messages without the MESSAGE Frame
When there is no content or message2 argument, predicates of expression are
annotated with EXPRESSION, and predicates of perception,
with EXPERIENCE.
Special Kinds of Messages
Gesture is a kind of expression, too:
Dependency graph for sentence: Kim shook their head no. Token shook is labeled MESSAGE-INIT and has an edge labeled SENDER to token Kim and an edge labeled NONCOMP to token head and an edge labeled content to token no.
For normative and evaluative messages, use NORM or EVALUATION, respectively.
EVALUATION
Roles: evaluee, evaluation
Special case of MESSAGE that involves an emotion or judgment of value or
expectedness about evaluee.
Dependency graph for sentence: The snake frightened them. Token frightened is labeled EVALUATION and has an edge labeled evaluee to token snake and an edge labeled EXPERIENCER to token them.
Dependency graph for sentence: Kim disapproved of it. Token disapproved is labeled EVALUATION and has an edge labeled EXPERIENCER to token Kim and an edge labeled evaluee to token it.
Dependency graph for sentence: Kim was pleased with Sandy. Token pleased is labeled EVALUATION and has an edge labeled EXPERIENCER to token Kim and an edge labeled evaluee to token Sandy.
Dependency graph for sentence: I was proud to have him learn that I could fly. Token proud is labeled EVALUATION and has an edge labeled EXPERIENCER to token I and an edge labeled evaluee to token learn.
Dependency graph for sentence: Fortunately for Kim , Sandy is here. Token Fortunately is labeled EVALUATION and has an edge labeled evaluee to token here. Token here is labeled LOCATION and has an edge labeled SCENE to token Fortunately and an edge labeled EXPERIENCER to token Kim and an edge labeled has-location to token Sandy.
Dependency graph for sentence: Of course I love you. Token Of is labeled EVALUATION and has an edge labeled evaluee to token love.
Predicates that encode an exclamative construction, expressing “a strong
emotional reaction to a propositional content” (Nivre et al.,
2026) or similar, can be annotated as
EVALUATION, too:
Dependency graph for sentence: How beautiful you are !. Token How is labeled EVALUATION and has an edge labeled evaluee to token beautiful.
NORM
Roles: norm-content, norm2
A special case of MESSAGE that does not make a descriptive claim, but is
about how things should be. This includes wishes, orders, goals, etc.
Dependency graph for sentence: Kim told Sandy to call. Token told is labeled META-NORM-INIT and has an edge labeled SENDER to token Kim and an edge labeled participant to token Sandy and an edge labeled scene to token call. Token call is labeled EXPRESSION and has an edge labeled sender to token Sandy.
Dependency graph for sentence: They are targeting a million in revenue. Token targeting is labeled NORM and has an edge labeled SENDER to token They and an edge labeled norm-content to token million.
Dependency graph for sentence: Kim wants to swim. Token wants is labeled META-NORM and has an edge labeled participant to token Kim and an edge labeled scene to token swim. Token swim is labeled LOCATION-DYN and has an edge labeled has-location to token Kim.
Dependency graph for sentence: Kim wants Sandy to swim. Token wants is labeled META-NORM and has an edge labeled EXPERIENCER to token Kim and an edge labeled participant to token Sandy and an edge labeled scene to token swim. Token swim is labeled LOCATION-DYN and has an edge labeled has-location to token Sandy.
Dependency graph for sentence: weit über das gesteckte Ziel hinausgehende Erfüllung. Token gesteckte is labeled NORM-INIT and has an edge labeled norm2 to token Ziel. Token Ziel is labeled ENTITY and has an edge labeled SCENE to token gesteckte. Token hinausgehende is labeled COMPARISON and has an edge labeled reference to token Ziel and an edge labeled compared to token Erfüllung. Token Erfüllung is labeled ENTITY and has an edge labeled SCENE to token hinausgehende.
Dependency graph for sentence: So then I chose another profession. Token chose is labeled NORM-INIT and has an edge labeled SCENE to token So and an edge labeled SCENE to token then and an edge labeled EXPERIENCER to token I and an edge labeled norm-content to token profession.
Dependency graph for sentence: Kim decided to play along. Token decided is labeled META-NORM-INIT and has an edge labeled participant to token Kim and an edge labeled scene to token play.
META
Roles: participant, scene
This frame is used to annotate control predicates where one dependent is
itself a predicate that assigns one or more other dependents a role. The former
gets the scene role, the latter get the participant role. The role assigned
by the scene must be annotated through an additional dependency from scene
to participant or one of its dependents (a “backlink”).
Dependency graph for sentence: Kim finished their work. Token finished is labeled META-DEINIT and has an edge labeled participant to token Kim and an edge labeled scene to token work. Token work is labeled SITUATION-DYN and has an edge labeled situee:hl to token Kim.
Dependency graph for sentence: Kim refrained from going. Token refrained is labeled META-PREVENTION and has an edge labeled participant to token Kim and an edge labeled scene to token going. Token going is labeled LOCATION-INIT and has an edge labeled has-location:hl to token Kim.
Dependency graph for sentence: Kim prevented Sandy from going. Token prevented is labeled META-PREVENTION and has an edge labeled CAUSER to token Kim and an edge labeled participant to token Sandy and an edge labeled scene to token going. Token going is labeled LOCATION-INIT and has an edge labeled has-location:hl to token Sandy.
Dependency graph for sentence: Kim used to ski. Token used is labeled META-HABIT-TIME and has an edge labeled participant to token Kim and an edge labeled scene to token ski. Token ski is labeled LOCATION-DYN and has an edge labeled has-location:hl to token Kim.
Dependency graph for sentence: The little prince did not dare confess he was sorry. Token dare is labeled META-INIT and has an edge labeled participant to token prince and an edge labeled SCENE to token not and an edge labeled scene to token confess. Token confess is labeled MESSAGE-INIT and has an edge labeled SENDER:hl to token prince and an edge labeled content to token sorry.
When the scene dependent is a noun, this is often called a light verb construction:
Dependency graph for sentence: Kim plays tennis. Token plays is labeled META and has an edge labeled participant to token Kim and an edge labeled scene to token tennis. Token tennis is labeled SITUATION-DYN and has an edge labeled situee:hl to token Kim.
Dependency graph for sentence: Winston machte nie den Versuch , das zu prüfen. Token machte is labeled META and has an edge labeled participant to token Winston and an edge labeled SCENE to token nie and an edge labeled scene to token Versuch. Token Versuch is labeled META-INIT and has an edge labeled participant:hl to token Winston and an edge labeled scene to token prüfen. Token prüfen is labeled MESSAGE-INIT and has an edge labeled EXPERIENCER:hl to token Winston and an edge labeled content to token das.
When a copula or auxiliary verb is promoted to syntactic head of a clause
because of ellipsis, it is also framed as META:
Dependency graph for sentence: How beautiful you are ! – Am I not ?. Token Am is labeled META and has an edge labeled participant to token I and an edge labeled SCENE to token not.
It is possible for scene to assign two different dependents of the META
predicate two different roles. The META predicate should assign both of them
the participant role:
Dependency graph for sentence: Kim gave Sandy a kick. Token gave is labeled META and has an edge labeled participant to token Kim and an edge labeled participant to token Sandy and an edge labeled scene to token kick. Token kick is labeled CONTACT-INIT and has an edge labeled CAUSER:hl to token Kim and an edge labeled surface:hl to token Sandy.
Dependency graph for sentence: Kim bekam Sandy zu fassen. Token bekam is labeled META-INIT and has an edge labeled participant to token Kim and an edge labeled participant to token Sandy and an edge labeled scene to token fassen. Token fassen is labeled POSSESSION and has an edge labeled possessor:hl to token Kim and an edge labeled possessum:hl to token Sandy.
On the other hand, META predicates may have arguments that are not members of
the embedded scene, such as CAUSER:
Dependency graph for sentence: Kim made Sandy dance. Token made is labeled META-INIT and has an edge labeled CAUSER to token Kim and an edge labeled participant to token Sandy and an edge labeled scene to token dance. Token dance is labeled POSE-DYN and has an edge labeled has-pose:hl to token Sandy.
The non-core role SCENE is used for adjectives, adverbs, and relative
clauses, which also assign their syntactic head a role, annotated through a
backlink:
Dependency graph for sentence: The clown I saw smiled. Token clown is labeled ENTITY and has an edge labeled SCENE to token saw. Token saw is labeled MESSAGE and has an edge labeled content:hl to token clown and an edge labeled EXPERIENCER to token I. Token smiled is labeled EXPRESSION and has an edge labeled sender to token clown.
Dependency graph for sentence: weit über das gesteckte Ziel hinausgehende Erfüllung. Token gesteckte is labeled NORM-INIT and has an edge labeled norm2:hl to token Ziel. Token Ziel is labeled ENTITY and has an edge labeled SCENE to token gesteckte. Token hinausgehende is labeled COMPARISON and has an edge labeled reference to token Ziel and an edge labeled compared:hl to token Erfüllung. Token Erfüllung is labeled ENTITY and has an edge labeled SCENE to token hinausgehende.
Dependency graph for sentence: Fortunately for Sandy , Kim is here. Token Fortunately is labeled EVALUATION and has an edge labeled EXPERIENCER to token Sandy and an edge labeled evaluee:hl to token here. Token here is labeled LOCATION and has an edge labeled SCENE to token Fortunately and an edge labeled has-location to token Kim.
Dependency graph for sentence: I devoted myself instead to geography. Token devoted is labeled BOND-INIT and has an edge labeled CAUSER to token I and an edge labeled tied to token myself and an edge labeled SCENE to token instead and an edge labeled tied-to to token geography. Token instead is labeled SUBSTITUTION and has an edge labeled substitute:hl to token devoted.
NONCOMP
Roles: has-noncomp, noncomp
Pseudoframe used to mark syntactic dependents that are part of a multiword predicate. Should only be used as a non-core role.
PERTINENCE
Roles: belongs, belongs-with
belongs belongs to or with belongs-with, typically in a not very precisely
specified sense.
This frame can be used, e.g., to annotate possessives that do not denote something more specific like literal possession or a part-whole relationship:
Dependency graph for sentence: my pocket. Token pocket is labeled ENTITY and has an edge labeled BELONGS-WITH to token my.
Dependency graph for sentence: my chair. Token chair is labeled ENTITY and has an edge labeled BELONGS-WITH to token my.
It can also be used to annotate adjectives that can be paraphrased as of or relating to X:
Dependency graph for sentence: mental effort. Token mental is labeled PERTINENCE and has an edge labeled belongs to token effort.
PART-WHOLE
Roles: part, whole
part is part of whole.
Dependency graph for sentence: Kim 's leg. Token leg is labeled ENTITY and has an edge labeled WHOLE to token Kim.
Dependency graph for sentence: a man with a mustache. Token man is labeled ENTITY and has an edge labeled PART to token mustache.
Dependency graph for sentence: wheat contains gluten. Token contains is labeled PART-WHOLE and has an edge labeled whole to token wheat and an edge labeled part to token gluten.
Dependency graph for sentence: The roots split the planet in pieces. Token split is labeled PART-WHOLE-INIT and has an edge labeled CAUSER to token roots and an edge labeled whole to token planet and an edge labeled part to token pieces.
For things like the entire planet or a whole herd of elephants, use QUANTITY instead:
Dependency graph for sentence: a whole herd of elephants. Token whole is labeled QUANTITY and has an edge labeled has-quantity to token herd.
Dependency graph for sentence: the entire planet. Token entire is labeled QUANTITY and has an edge labeled has-quantity to token planet.
INSTANCE
Roles: instance, class
instance is an element or subset of the set denoted by class.
Dependency graph for sentence: It was a picture of a boa constrictor. Token picture is labeled MESSAGE and has an edge labeled INSTANCE to token It and an edge labeled content to token boa.
Dependency graph for sentence: Fido is a dog. Token dog is labeled ENTITY and has an edge labeled INSTANCE to token Fido.
Dependency graph for sentence: The object instantiates the class. Token instantiates is labeled INSTANCE and has an edge labeled instance to token object and an edge labeled class to token class.
Dependency graph for sentence: one of them. Token one is labeled INSTANCE and has an edge labeled class to token them.
Dependency graph for sentence: vehicles such as cars. Token vehicles is labeled ENTITY and has an edge labeled INSTANCE to token cars.
Dependency graph for sentence: Pferde gehören zu den Unpaarhufern. Token gehören is labeled INSTANCE and has an edge labeled instance to token Pferde and an edge labeled class to token Unpaarhufern.
Dependency graph for sentence: two of them. Token two is labeled INSTANCE and has an edge labeled class to token them.
Dependency graph for sentence: understanding is a kind of ecstasy. Token kind is labeled INSTANCE and has an edge labeled instance to token understanding and an edge labeled class to token ecstasy.
Dependency graph for sentence: a herd of elephants. Token herd is labeled INSTANCE and has an edge labeled instance to token elephants.
MATERIAL
Roles: material, object
A special case of PART-WHOLE where object does not just
contain material, but is said to be made from it.
Dependency graph for sentence: the sculpture is made from stone. Token made is labeled MATERIAL and has an edge labeled object to token sculpture and an edge labeled material to token stone.
Dependency graph for sentence: it consists of wood. Token consists is labeled MATERIAL and has an edge labeled object to token it and an edge labeled material to token wood.
SUBSCENE
Roles: subscene, superscene
A part-whole relationship that holds between two scenes (i.e., eventualities,
i.e., states or events). subscene is part of the superscene.
Dependency graph for sentence: The party began with a speech. Token began is labeled SUBSCENE and has an edge labeled superscene to token party and an edge labeled subscene to token speech.
Dependency graph for sentence: Kim began the party with a speech. Token began is labeled SUBSCENE and has an edge labeled CAUSER to token Kim and an edge labeled superscene to token party and an edge labeled subscene to token speech. Token speech is labeled EXPRESSION and has an edge labeled sender to token Kim.
Dependency graph for sentence: in the course of this life. Token course is labeled SUBSCENE and has an edge labeled superscene to token life.
Dependency graph for sentence: This ship is already very sickly. Token already is labeled SUBSCENE and has an edge labeled subscene to token sickly.
Dependency graph for sentence: I would learn , in our talk , something about the little prince ’s planet. Token learn is labeled MESSAGE-INIT and has an edge labeled EXPERIENCER to token I and an edge labeled SUPERSCENE to token talk and an edge labeled content to token something.
DYN
Roles: stage, process
process is a dynamic process involving possibly multiple occurrences of
stage.
This frame and its subframes are used extensively in annotating dynamic predicates – they “convert” from the basic frames, which all denote states, to stacked frames denoting dynamic processes.
Apart from that DYN can also be used for adjectives and adverbs that modify a
process-denoting predicate and describe its internal unfolding over stages:
Dependency graph for sentence: fumble along. Token along is labeled DYN and has an edge labeled process to token fumble.
Dependency graph for sentence: Bit by bit I came to understand the secrets of your sad little life. Token Bit is labeled DYN and has an edge labeled NONCOMP to token bit and an edge labeled process to token came.
Dependency graph for sentence: She adjusted her petals one by one. Token one is labeled DYN and has an edge labeled process to token adjusted and an edge labeled NONCOMP to token one.
Dependency graph for sentence: The change was gradual. Token gradual is labeled DYN and has an edge labeled process to token change.
CONTINUATION
Roles: continued, continuation
continuation is an event with continued as an initial subeventuality that
continues throughout continuation.
For examples, see the chapter on Annotating Dynamic Verbs.
DEINIT
Roles: deinitiated, deinitiation
deinitiation is an event with deinitiated as an initial subeventuality,
acting towards the end of deinitiated.
For examples, see the chapter on Annotating Dynamic Verbs.
HABIT
Roles: habitual, habit
habit is an event with habitual as a frequent or usual subeventuality.
For examples, see the chapter on Annotating Dynamic Verbs.
INIT
Roles: initiated, initiation
initiation is an event acting towards the bringing about of initiated,
with initiated as a possible final subeventuality.
For examples, see the chapter on Annotating Dynamic Verbs.
PREVENTION
Roles: prevented, prevention
prevention is an event as part of which the eventuality prevented fails to
come about.
For examples, see the chapter on Annotating Dynamic Verbs.
TRANSIT
Roles: transitory, transition
transition is an event during which the eventuality transitory comes about
and ends, possibly repeatedly.
For examples, see the chapter on Annotating Dynamic Verbs.
SOCIAL-RELATION
Roles: socially-related, socially-related-to
socially-related is socially related to socially-related-to with no clear
hierarchy. Use BOND otherwise.
Dependency graph for sentence: Kim 's friend. Token friend is labeled SOCIAL-RELATION and has an edge labeled socially-related to token Kim.
Dependency graph for sentence: Kim is my cousin. Token cousin is labeled SOCIAL-RELATION and has an edge labeled socially-related-to to token Kim and an edge labeled socially-related to token my.
Dependency graph for sentence: Kim and Sandy are friends. Token friends is labeled SOCIAL-RELATION and has an edge labeled socially-related to token Kim.
Dependency graph for sentence: Kim married Sandy. Token married is labeled SOCIAL-RELATION-INIT and has an edge labeled socially-related to token Kim and an edge labeled socially-related-to to token Sandy.
Dependency graph for sentence: The official married Kim to Sandy. Token married is labeled SOCIAL-RELATION-INIT and has an edge labeled CAUSER to token official and an edge labeled socially-related to token Kim and an edge labeled socially-related-to to token Sandy.
Dependency graph for sentence: The official married Kim and Sandy. Token married is labeled SOCIAL-RELATION-INIT and has an edge labeled CAUSER to token official and an edge labeled socially-related to token Kim.
Dependency graph for sentence: Kim divorced Sandy. Token divorced is labeled SOCIAL-RELATION-DEINIT and has an edge labeled socially-related to token Kim and an edge labeled socially-related-to to token Sandy.
Dependency graph for sentence: Kim befriended Sandy. Token befriended is labeled SOCIAL-RELATION-INIT and has an edge labeled socially-related to token Kim and an edge labeled socially-related-to to token Sandy.
BOND
Roles: tied, tied-to
A SOCIAL-RELATION that can be framed as a bond, tie, or obligation of an individual to another individual, group, office, task, punishment, etc.
Dependency graph for sentence: Kim works at Google. Token works is labeled BOND and has an edge labeled tied to token Kim and an edge labeled tied-to to token Google.
Dependency graph for sentence: Kim works for Sandy. Token works is labeled BOND and has an edge labeled tied to token Kim and an edge labeled tied-to to token Sandy.
Dependency graph for sentence: Kim emcees. Token emcees is labeled BOND and has an edge labeled tied to token Kim.
Dependency graph for sentence: Kim is hosting the part. Token hosting is labeled BOND and has an edge labeled tied to token Kim and an edge labeled tied-to to token part.
Dependency graph for sentence: Kim is under house arrest. Token arrest is labeled BOND and has an edge labeled tied to token Kim.
Dependency graph for sentence: Kim 's sentence was suspended. Token sentence is labeled BOND and has an edge labeled tied to token Kim.
Dependency graph for sentence: Kim took the job. Token took is labeled META-INIT and has an edge labeled participant to token Kim and an edge labeled scene to token job. Token job is labeled BOND and has an edge labeled tied to token Kim.
Dependency graph for sentence: Kim joined Google. Token joined is labeled BOND-INIT and has an edge labeled tied to token Kim and an edge labeled tied-to to token Google.
Dependency graph for sentence: Sandy fired Kim from their job. Token fired is labeled BOND-DEINIT and has an edge labeled CAUSER to token Sandy and an edge labeled tied to token Kim and an edge labeled tied-to to token job.
Dependency graph for sentence: Kim left Google. Token left is labeled BOND-DEINIT and has an edge labeled tied to token Kim and an edge labeled tied-to to token Google.
Dependency graph for sentence: Kim assumed office. Token assumed is labeled BOND-INIT and has an edge labeled tied to token Kim and an edge labeled tied-to to token office.
Dependency graph for sentence: The judge sentenced Kim to three days in prison. Token sentenced is labeled BOND-INIT and has an edge labeled CAUSER to token judge and an edge labeled tied-to to token days.
Dependency graph for sentence: Kim was pardoned. Token pardoned is labeled BOND-DEINIT and has an edge labeled tied to token Kim.
POSSESSION
Roles: possessum, possessor
possessor possesses possessum, i.e, has control over it through power and
opportunity or through a social construct such as law.
Dependency graph for sentence: Kim 's house. Token house is labeled ENTITY and has an edge labeled POSSESSOR to token Kim.
Dependency graph for sentence: Kim owns a house. Token owns is labeled POSSESSION and has an edge labeled possessor to token Kim and an edge labeled possessum to token house.
Dependency graph for sentence: The house belongs to Kim. Token belongs is labeled POSSESSION and has an edge labeled possessum to token house and an edge labeled possessor to token Kim.
Dependency graph for sentence: the owner of the house. Token owner is labeled POSSESSION and has an edge labeled possessum to token house.
Dependency graph for sentence: Kim has Sandy 's phone. Token has is labeled POSSESSION and has an edge labeled possessor to token Kim and an edge labeled possessum to token phone. Token phone is labeled ENTITY and has an edge labeled POSSESSOR to token Sandy.
Dependency graph for sentence: Kim bought a house from Sandy. Token bought is labeled POSSESSION-INIT and has an edge labeled possessor to token Kim and an edge labeled possessum to token house and an edge labeled possessor-DEINIT to token Sandy.
Dependency graph for sentence: Sandy sold Kim the house. Token sold is labeled POSSESSION-DEINIT and has an edge labeled possessor to token Sandy and an edge labeled possessor-INIT to token Kim and an edge labeled possessum to token house.
Dependency graph for sentence: Kim kept the house. Token kept is labeled POSSESSION-CONTINUATION and has an edge labeled possessor to token Kim and an edge labeled possessum to token house.
Dependency graph for sentence: Kim lost the house. Token lost is labeled POSSESSION-DEINIT and has an edge labeled possessor to token Kim and an edge labeled possessum to token house.
Dependency graph for sentence: Caesar conquered Gaul. Token conquered is labeled POSSESSION-INIT and has an edge labeled possessor to token Caesar and an edge labeled possessum to token Gaul.
Dependency graph for sentence: Caesar 's conquest of Gaul. Token conquest is labeled POSSESSION-INIT and has an edge labeled possessor to token Caesar and an edge labeled possessum to token Gaul.
Dependency graph for sentence: Kim owes Sandy money. Token owes is labeled POSSESSION-DEINIT-NECESSITY and has an edge labeled possessor to token Kim and an edge labeled possessor-INIT-NECESSITY to token Sandy and an edge labeled possessum to token money.
REGARD
Roles: has-regard, regard
Used for dependents that are in a semantic relation not so much with their head
but with one or more of its dependents (or a descendant of one). A backlink is
required from the former to the latter. When unsure which of two dependents to
annotate with REGARD, choose the more
oblique one.
Dependency graph for sentence: Kim exceeds Sandy in height. Token exceeds is labeled COMPARISON and has an edge labeled compared to token Kim and an edge labeled reference to token Sandy and an edge labeled REGARD to token height. Token height is labeled PROPERTY and has an edge labeled has-property:hl to token Kim and an edge labeled has-property:hl to token Sandy.
Dependency graph for sentence: That is great in terms of ROI. Token great is labeled PROPERTY and has an edge labeled has-property to token That and an edge labeled SCENE to token terms. Token terms is labeled REGARD and has an edge labeled has-regard to token great and an edge labeled regard to token ROI. Token ROI is labeled PROPERTY and has an edge labeled has-property:hl to token That.
Dependency graph for sentence: Kim ist auf den Kopf gefallen. Token Kopf is labeled ENTITY and has an edge labeled WHOLE:hl to token Kim. Token gefallen is labeled CONTACT-INIT and has an edge labeled ornament to token Kim and an edge labeled REGARD to token Kopf.
Dependency graph for sentence: Kim hit Sandy on the head with a stick. Token hit is labeled CONTACT-INIT and has an edge labeled CAUSER to token Kim and an edge labeled surface to token Sandy and an edge labeled REGARD to token head and an edge labeled ornament to token stick. Token head is labeled ENTITY and has an edge labeled WHOLE:hl to token Sandy.
Dependency graph for sentence: Something was broken in my engine. Token broken is labeled INTERNAL-STATE and has an edge labeled has-state to token Something and an edge labeled REGARD to token engine. Token engine is labeled ENTITY and has an edge labeled PART:hl to token Something and an edge labeled POSSESSOR to token my.
Dependency graph for sentence: Er wandte dem Televisor den Rücken zu. Token wandte is labeled ORIENTATION and has an edge labeled oriented to token Er and an edge labeled landmark to token Televisor and an edge labeled REGARD to token Rücken. Token Rücken is labeled ENTITY and has an edge labeled WHOLE:hl to token Er.
TIME
Roles: has-time, time
Indicates when, how often, or for how long has-time takes place relative to
time, which may be a point or span in time, or another event.
Dependency graph for sentence: Kim swims on Mondays. Token swims is labeled LOCATION-DYN and has an edge labeled has-location to token Kim and an edge labeled TIME to token Mondays.
Dependency graph for sentence: Kim sneezed twice. Token twice is labeled TIME and has an edge labeled has-time to token sneezed.
Dependency graph for sentence: Kim swam for an hour. Token swam is labeled LOCATION-DYN and has an edge labeled has-location to token Kim and an edge labeled TIME to token hour.
Dependency graph for sentence: Kim says hello whenver I meet them. Token says is labeled MESSAGE-INIT and has an edge labeled SENDER to token Kim and an edge labeled content to token hello and an edge labeled TIME to token meet.
Dependency graph for sentence: Die Hassovation dauert 30 Sekunden. Token dauert is labeled TIME and has an edge labeled has-time to token Hassovation and an edge labeled time to token Sekunden.
Dependency graph for sentence: Once when I was six years old. Token Once is labeled TIME and has an edge labeled has-time to token old. Token when is labeled TIME and has an edge labeled time to token old.
Dependency graph for sentence: a moment of complete silence. Token moment is labeled TIME and has an edge labeled has-time to token silence.
AGE
Roles: has-age, age
Special case of TIME that is about for how long somebody or something has
existed.
Dependency graph for sentence: I am old. Token old is labeled AGE and has an edge labeled has-age to token I.
Dependency graph for sentence: I am six years old. Token old is labeled AGE and has an edge labeled has-age to token I and an edge labeled age to token years.
SEQUENCE
Roles: follows, followed
follows and followed are two related eventualities – or, by metonymy,
participants in related eventualities – where (barring unusual circumstances
such as time travel) follows follows followed in time, but they are not
only related temporally, but also logically, in the sense that followed sets
up some kind of expectation of follows or its possibility.
Dependency graph for sentence: Abruptly , without anything to lead up to it , he demanded: Does it eat flowers , too ?. Token lead is labeled SEQUENCE and has an edge labeled followed to token anything and an edge labeled follows to token it.
COPY
Roles: copy, original
copy occurs similarly to or is created after the model of (but can differ
from) original.
Dependency graph for sentence: Here is a copy of the drawing. Token copy is labeled COPY and has an edge labeled original to token drawing.
Dependency graph for sentence: Kim translated of the pamphlet into English. Token translated is labeled COPY-INIT and has an edge labeled CAUSER to token Kim and an edge labeled original to token pamphlet and an edge labeled PROPERTY to token English.
Dependency graph for sentence: It is less charming that its model. Token model is labeled COPY and has an edge labeled copy to token its.
Dependency graph for sentence: So then I did my drawing over once more. Token over is labeled COPY and has an edge labeled copy to token did.
Dependency graph for sentence: the astronomer gave his presentation all over again. Token over is labeled COPY and has an edge labeled copy to token gave. Token again is labeled COPY and has an edge labeled copy to token gave.
Dependency graph for sentence: It is for that purpose , again , that I have bought a box of paints and some pencils. Token again is labeled COPY and has an edge labeled copy to token purpose.
Dependency graph for sentence: With that , Kim repeated their old mistake. Token that is labeled ENTITY and has an edge labeled CAUSER to token Kim. Token repeated is labeled COPY-INIT and has an edge labeled copy to token that and an edge labeled CAUSER to token Kim and an edge labeled original to token mistake. Token mistake is labeled ENTITY and has an edge labeled CAUSER to token their.
Dependency graph for sentence: I took up drawing again. Token again is labeled COPY and has an edge labeled copy to token took.
FULFILMENT
Roles: fulfiller, fulfilled
fulfilled is a promise or expectation or plan, etc., that is fulfilled by
fulfiller.
Dependency graph for sentence: Kim kept their word. Token kept is labeled FULFILMENT-INIT and has an edge labeled CAUSER to token Kim and an edge labeled fulfilled to token word.
Dependency graph for sentence: Kim disobeyed the order. Token disobeyed is labeled FULFILMENT-PREVENTION and has an edge labeled CAUSER to token Kim and an edge labeled fulfilled to token order.
Dependency graph for sentence: I finally succeeded in making my first drawing. Token succeeded is labeled META-FULFILMENT-INIT and has an edge labeled participant to token I and an edge labeled scene to token making.
Dependency graph for sentence: the failure of my Drawing Number One. Token failure is labeled FULFILMENT-PREVENTION and has an edge labeled fulfilled to token Drawing.
Dependency graph for sentence: But with the others I have not been successful. Token successful is labeled FULFILMENT and has an edge labeled fulfilled to token others and an edge labeled CAUSER to token I and an edge labeled SCENE to token not.
SUBSTITUTION
Roles: substitute, replaced
replaced is replaced with substitute.
Dependency graph for sentence: Sandy replaced Kim with AI. Token replaced is labeled SUBSTITUTION-INIT and has an edge labeled replaced to token Kim and an edge labeled substitute to token AI.
Dependency graph for sentence: Kim substituted an L for the asterisk. Token substituted is labeled SUBSTITUTION-INIT and has an edge labeled CAUSER to token Kim and an edge labeled substitute to token L and an edge labeled replaced to token asterisk.
References
Joakim Nivre, William Croft, André V. Lopes Coneglian (2026). Speech Act Constructions in Universal Dependencies. In Proceedings of the 9th Workshop on Universal Dependencies (UDW). Association for Computational Linguistics.
William Croft (2022). Morphosyntax: constructions of the world’s languages. Cambridge University Press.
Leon Stassen (1997). Intransitive Predication. Oxford University Press.