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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,

  1. Superframes does not require a lexicon. Frames are coarse and small enough in number to learn them by heart.
  2. Superframes is language-independent.
  3. 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 sentences 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. For consistency, there is a rule that says predicates with no core arguments must always be annotated with the most general superframe ENTITY. So that is what happens for example for weather verbs such as rain (which has a syntactic, but semantically empty argument):

Dependency graph for sentence: It is raining. Token raining is labeled ENTITY and has an edge labeled NONCOMP to token It.

We will turn to what NONCOMP means later.

Annotating Dynamic Verbs

Many predicates, especially verbs, do not simply denote a state. Rather, they denote a process working towards the coming about of a state, or a process working against the coming about of a state, or the continuation of a state, or a process working towards the end of a state, or a habitual repeated coming about of a state, or the transitioning through a state, or even a process that transitions through a multitude of states.

Using Aspectual Frames

Superframes inidicates this kind of dynamism through a number of special frames that we call aspectual frames: INIT, PREVENTION, CONTINUATION, DEINIT, HABIT, TRANSIT, DYN. They are combined with ordinary frames through a mechanism called frame stacking. For example:

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.

Here, the predicate got has been annotated with the POSSESSION frame, with Kim as possessor and the house as possessum, as we have seen before. What is new is that the INIT frame has been stacked onto the POSSESSION frame, indicating that the verb denotes not the state of possession, but a process working towards it.

Note

On a technical level, frame stacking indicates that the first frame – here: POSSESSION – fills the first role of the second frame – here: INIT.

Further examples of INIT include:

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: 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.

The DEINIT frame indicates a process working towards the end of a state:

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 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 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.

The TRANSIT frame indicates a process that transitions through a state where the state does not necessarily exist at the beginning or the end:

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.

The CONTINUATION frame indicates that a state persists:

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 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.

The PREVENTION frame indicates that a state fails to come about:

Dependency graph for sentence: Kim was saved from the dragon. Token saved is labeled INFLUENCE-PREVENTION and has an edge labeled influenced to token Kim and an edge labeled influence to token dragon.

The HABIT frame indicates that a state comes about repeatedly, or exists normally:

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.

Finally, the DYN frame indicates a process that is not straightforwardly described in terms of one or more specific states but instead is a complex process transitioning through a multitude of states. Because these states can be very heterogeneous, we usually stack DYN on top of the very general SITUATION frame.

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 phases of the process. 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

Some verbs take another predicate (more precisely: a phrase headed by another predicate) as an argument and contribute an aspectual meaning. We call such predicates matrix predicates, taking an embedded predicate. In such cases, use aspectual frames 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 matrix verbs take over the syntactic subject of their embedded predicate in what is known as a control construction. In such cases, we stack an aspectual frame over the special META frame. Its scene role is filled by the embedded predicate, and its participant role is filled by the controlled subject. It is then required to add a semantic dependency from the embedded predicate to the controlled subject, even though no such syntactic dependency exists in (basic) UD.

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 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 the superframe that the predicate is annotated with (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

On a technical level, the non-core CAUSATION frame is interpreted as being added “around” the core INTERNAL-STATE-INIT frame so that the latter fills the former other role (the effect role). This makes sense: the vase breaking is the effect here.

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 topic to token Bali.

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 topic 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 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.

Relational nouns are not much different, except that they additionally refer to one of the participants in the relation. But we are only concerned with evocation, not with reference.

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.

When used in predicative function in copula clauses, relational nouns assign a role to the subject:

Dependency graph for sentence: He is our physics teacher. Token teacher is labeled MESSAGE-HABIT and has an edge labeled SENDER to token He and an edge labeled EXPERIENCER to token our and an edge labeled topic 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 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 to token Sandy and an edge labeled existent to token city.

Many nouns, of course, are neither event nouns nor relational nouns, and thus do not have any (core) arguments. The includes proper nouns and is also true for most pronouns. 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.

Occasionally, pronouns do have arguments. In that case, frame them like you would the antecedent:

Dependency graph for sentence: The picture was that of the boa. Token that is labeled MESSAGE and has an edge labeled SAME to token picture and an edge labeled topic to token boa. 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 and has an edge labeled experiencer to token astronomer. Token astronomer is labeled ENTITY and has an edge labeled SCENE to token That and an edge labeled SCENE to token Turkish and an edge labeled TIME to token 1909.

When used with a non-event, non-relational noun, the copula construction assigns INSTANCE to the subject if predicative, and SAME if equational (cf. Stassen 1997, p. 100–6; Croft 2022, § 10.1.2):

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 topic to token boa. Dependency graph for sentence: Baobabs were not little bushes. Token bushes is labeled ENTITY and has an edge labeled INSTANCE to token Baobabs and an edge labeled SCENE to token little. 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 to token planet and an edge labeled SCENE to token known.

With adpositions, the copula construction can assign different roles still:

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 to token sprout and an edge labeled SCENE to token not and an edge labeled SCENE to token small and an edge labeled LOCATION to token planet.

Annotating Nominal Modifiers, Oblique Nominals, and Adverbial Clauses

Both nominal modifiers (nmod, nmod:poss) and oblique nominals (obl) can be annotated as part of the argument structure of their head, as core or non-core arguments:

Dependency graph for sentence: a book about the primeval forest. Token book is labeled MESSAGE and has an edge labeled topic 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. Dependency graph for sentence: my friend. Token friend is labeled SOCIAL-RELATION and has an edge labeled socially-related to token my. Dependency graph for sentence: after that they are not able to move. Token able is labeled META-POSSIBILITY and has an edge labeled TIME to token that and an edge labeled participant to token they and an edge labeled scene to token move. 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: 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 topic to token masterpiece and an edge labeled EXPERIENCER to token grown-ups. Dependency graph for sentence: the grown-ups’ response. Token response is labeled SENDING and has an edge labeled sender to token grown-ups’. Dependency graph for sentence: his level. Token level is labeled PROPERTY and has an edge labeled has-property to token his. 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: That is my fault. Token fault is labeled CAUSATION and has an edge labeled effect to token That and an edge labeled causer 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: my judge. Token judge is labeled EVALUATION and has an edge labeled evaluee to token my.

If they are not part of the argument structure, they should be annotated just like non-core arguments – or, as it were, as non-core arguments, because we do not attempt to dinstiguish between the two cases. The same goes for adverbial clauses (advcl):

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 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 to token Kinder. Dependency graph for sentence: gekommen , um zu bleiben. Token gekommen is labeled LOCATION-INIT and has an edge labeled END to token bleiben. Dependency graph for sentence: a tree in the garden. Token tree is labeled ENTITY and has an edge labeled LOCATION to token garden. Dependency graph for sentence: Kim ’s tree. Token tree is labeled ENTITY and has an edge labeled POSSESSOR to token Kim. Dependency graph for sentence: my car. Token car is labeled ENTITY and has an edge labeled POSSESSOR to token my. Dependency graph for sentence: my feet. Token feet is labeled ENTITY and has an edge labeled WHOLE to token my.

Annotating Adjectives, Adverbs, and Relative Clauses

Predicative Adjectives

Predicative adjectives are annotated much like verbs:

Dependency graph for sentence: I am despicable. Token despicable is labeled PROPERTY and has an edge labeled has-property to token I. Dependency graph for sentence: The dog is tired. Token tired is labeled INTERNAL-STATE and has an edge labeled has-state to token dog. Dependency graph for sentence: Change is necessary. Token necessary is labeled NECESSITY and has an edge labeled necessary to token Change. Dependency graph for sentence: Change is possible. Token possible is labeled POSSIBILITY and has an edge labeled possible to token Change.

Attributive Adjectives and Adverbs

Attributive adjectives and adverbs behave syntactically like modifiers, but they are also predicates assigning the modifiee a role. For the modification relation, we use the META frame, assigning the modifying predicate the scene role and – implicitly – the modifiee the participant role. We then introduce an additional semantic dependency (we call it a backlink) from the modifying predicate to the modifiee to annotate the role that the former assigns to the latter. For example:

Dependency graph for sentence: despicable me. Token despicable is labeled PROPERTY and has an edge labeled has-property to token me. Token me is labeled ENTITY and has an edge labeled SCENE to token despicable. Dependency graph for sentence: the tired dog. Token tired is labeled INTERNAL-STATE and has an edge labeled has-state to token dog. Token dog is labeled ENTITY and has an edge labeled SCENE to token tired. 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 to token fast. Token fast is labeled PROPERTY and has an edge labeled has-property 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 to token far. Token far is labeled QUANTITY and has an edge labeled has-quantity 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 to token lieber and an edge labeled scene to token Schach. Token lieber is labeled EVALUATION and has an edge labeled evaluee 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 to token kaputt. Token kaputt is labeled INTERNAL-STATE and has an edge labeled has-state to token Der and an edge labeled SCENE to token sowieso. Dependency graph for sentence: Und doch sah er intelligent aus. Token doch is labeled CONCESSION and has an edge labeled asserted to token sah. Token sah is labeled MESSAGE and has an edge labeled SCENE to token doch and an edge labeled topic to token er and an edge labeled message 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 to token ungeachtet and an edge labeled LOCATION to token draußen. Token ungeachtet is labeled CONCESSION and has 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 to token fröhlich. Token fröhlich is labeled INTERNAL-STATE and has an edge labeled has-state to token Kim and an edge labeled SCENE 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 to token Hilfe and an edge labeled SCENE to token so. Token so is labeled SENDING and has an edge labeled sent to token gebeten and an edge labeled sender to token Saqib. Dependency graph for sentence: ein anderes Plakat. Token anderes is labeled COMPARISON and has an edge labeled compared to token Plakat. Token Plakat is labeled ENTITY and has an edge labeled SCENE to token anderes.

Dynamic Adverbs

Dynamic adverbs, like dynamic verbs, are annotated using aspectual frames with stacking:

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 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 to token myself and an edge labeled has-property to token his.

Relative Clauses

Relative clauses work very similarly: they modify a noun but also act as predicates assigning that noun a role. Again, we use SCENE for the acl:relcl relation, and a backlink to the modified noun. This is in addition to the dependency to any relative pronoun, which has the same role.

Dependency graph for sentence: the song that I like. Token song is labeled ENTITY and has an edge labeled EXPERIENCER to token I and an edge labeled SCENE to token like. Token like is labeled EVALUATION and has an edge labeled evaluee to token song and an edge labeled evaluee to token that. Dependency graph for sentence: the song I like. Token song is labeled ENTITY and has an edge labeled EXPERIENCER to token I and an edge labeled SCENE to token like. Token like is labeled EVALUATION and has an edge labeled evaluee to token song.

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 in the previous chapter with attributive adjectives, adverbs, and relative clauses: these elements are attached to their head using the META frame (manifesting as a SCENE modifying relation), and then a nonlocal dependency (a “backlink”) is added from the modifying element back to its head.

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 NORM-INIT and has an edge labeled SENDER to token Kim and an edge labeled EXPERIENCER to token Sandy and an edge labeled norm to token come. Token come is labeled LOCATION-INIT and has an edge labeled has-location to token Kim. Dependency graph for sentence: Kim used a hammer to smash the vase. Token used is labeled MEANS and has an edge labeled CAUSER to token Kim and an edge labeled means to token hammer and an edge labeled end to token smash. Token smash is labeled INTERNAL-STATE-INIT and has an edge labeled CAUSER to token Kim and an edge labeled has-state to token vase.

Object control:

Dependency graph for sentence: Kim persuaded Sandy to come. Token persuaded is labeled NORM-INIT and has an edge labeled SENDER to token Kim and an edge labeled EXPERIENCER to token Sandy and an edge labeled norm to token come. Token come is labeled LOCATION-INIT and has an edge labeled has-location to token Sandy.

Non-obligatory control:

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 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 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 to token prince and an edge labeled scene to token doubt.

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 message 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 topic to token question and an edge labeled SENDER to token we.

Raising:

Dependency graph for sentence: Kim seemed to fly. Token seemed is labeled MESSAGE and has an edge labeled topic to token Kim and an edge labeled message to token fly. Token fly is labeled LOCATION-DYN and has an edge labeled has-location to token Kim.

Secondary predicate (see also the section on secondary predicates below):

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 SENDING and has an edge labeled sender to token Kim.

Tough construction:

Dependency graph for sentence: Kim is hard to love. Token hard is labeled META-REALITY 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 to token Kim.

Relative clause:

Dependency graph for sentence: the song that I like. Token song is labeled ENTITY and has an edge labeled EXPERIENCER to token I and an edge labeled SCENE to token like. Token like is labeled EVALUATION and has an edge labeled evaluee to token song and an edge labeled evaluee to token that.

Reduced relative clause:

Dependency graph for sentence: the song I like. Token song is labeled ENTITY and has an edge labeled EXPERIENCER to token I and an edge labeled SCENE to token like. Token like is labeled EVALUATION and has an edge labeled evaluee to token song.

Non-finite reduced relative clause:

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 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 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 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 EXPERIENCER to token man and an edge labeled SCENE-NECESSITY to token talk. Token talk is labeled SENDING.

Relative clause with complex extracted element:

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 to token Gestalt. Token noch is labeled ACCOMPANIMENT and has an edge labeled accompanier to token betont. Token betont is labeled MESSAGE and has an edge labeled topic to token Magerkeit and an edge labeled SENDER to token Trainingsanzug and an edge labeled SCENE to token noch.

Relative clause with extraction across clause boundaries:

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 to token Atmosphäre and an edge labeled situator to token der 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.

In cleft sentences (including wh-cleft/pseudocleft), annotate the clausal subject with the SCENE role:

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 to token words and an edge labeled topic to token everything and an edge labeled EXPERIENCER to token me. 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 and has an edge labeled experiencer to token astronomer. Token astronomer is labeled ENTITY and has an edge labeled SCENE to token That and an edge labeled SCENE to token Turkish and an edge labeled TIME to token 1909.

Coordination:

Dependency graph for sentence: ein sogenannter Televisor oder Hörsehschirm. Token sogenannter is labeled IDENTIFIER-INIT and has an edge labeled identified to token Televisor and an edge labeled identified 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 to token sogenannter.

Secondary Predicates

Secondary predicates are modifiers that syntactically attach to a (primary) predicate, but semantically predicate over one of the primary predicate’s arguments, or even something more deeply embedded. The semantic relation between the primary and the secondary predicate can be one of simple accompaniment (these secondary predicates are also called depictives), effect (these secondary predicates are also called resultatives), or something else.

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 SENDING and has an edge labeled sender to token Kim. 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 topic to token sheep. Token small is labeled PROPERTY and has an edge labeled has-property to token sheep. Token big is labeled PROPERTY and has an edge labeled has-property 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 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. 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 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 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 SENDING and has an edge labeled sender to token You and an edge labeled EFFECT to token me and an edge labeled EFFECT to token silly. Token silly is labeled INTERNAL-STATE and has an edge labeled has-state to token me.

Note that in the resultative example You’re talking me silly, the primary predicate talking does not assign a role to its syntactic object me, only the secondary predicate silly does. But the annotation scheme still forces us to label the dependency from talking to me. We solve this by labeling it EFFECT too, just like the dependency to the secondary predicate.

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 influenced. Thus:

Dependency graph for sentence: It is not important. 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.

Prefer to Avoid Stacking

If something could be framed with either a single frame or two stacked frames, prefer using a single frame.

Thus:

Dependency graph for sentence: Kim seems happy. Token seems is labeled MESSAGE and has an edge labeled topic to token Kim and an edge labeled message to token happy.

Rather than:

Dependency graph for sentence: Kim seems happy. Token seems is labeled META-REALITY and has an edge labeled participant to token Kim and an edge labeled scene to token happy.

Prefer More Specific Frames

If not sure which of two frames to use, tend to prefer the more specific one. For example, if TIME and CONDITION would both fit and you feel that CONDITION is more specific, prefer CONDITION:

Dependency graph for sentence: Then I would never talk to them about boa constrictors. Token Then is labeled CONDITION and has an edge labeled has-condition to token constrictors.

Similarly, if an argument can be seen as assigning a role to another argument, it is better to use META than, e.g., SITUATION:

Dependency graph for sentence: He buried himself in the contemplation of his treasure. Token buried is labeled META-INIT and has an edge labeled participant to token himself and an edge labeled scene to token contemplation. Token contemplation is labeled MESSAGE-INIT and has an edge labeled EXPERIENCER to token himself and an edge labeled topic to token treasure.

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 annotation rules make reference to obliqueness, a concept used to rank dependents by the syntactic “coreness” of their role. For our purposes, nsubj dependents are least oblique, followed by obj, followed by iobj, followed by obl.

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).

TermExplanation
adjunctD 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
argumentD 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
dependentif 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)
eventa synonym for eventuality; sometimes also used as a synonym for process; I try to avoid the term due to its ambiguity
eventualitya state or process
headH is a head of D iff D is a dependent of H
predicatea content word (noun, verb, adjective, or adverb) that evokes a frame
processa dynamic eventuality, i.e., a transition over time through two or more states
scenea synonym for eventuality
situationa synonym for eventuality
statea 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 MESSAGE and has an edge labeled EXPERIENCER to token I and an edge labeled topic to token light and an edge labeled message to token break. Token break is labeled SENDING-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 topic 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 los. Token los 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.

COMPARISON

Roles: compared, reference

compared is characterized with respect to reference.

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 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 SENDING 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 SENDING 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.

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 SENDING 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: 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 topic 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 SENDING and has an edge labeled sender to token he and an edge labeled SAME-AS 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-AS to token answer and an edge labeled SENDER to token he and an edge labeled message to token draw.

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 to token Kim and an edge labeled has-property 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. 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 to token That. Dependency graph for sentence: Kim ist auf den Kopf gefallen. Token Kopf is labeled ENTITY and has an edge labeled WHOLE 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 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 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 to token Er.

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: influenced, influence

influence is or exerts an influence over influenced.

Dependency graph for sentence: Kim was saved from the dragon. Token saved is labeled INFLUENCE-PREVENTION and has an edge labeled influenced 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 influenced 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 influenced 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.

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.

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 message 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 topic 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 message 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 topic 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 topic 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 SENDING-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 message 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.

SENDING

Roles: sent, sender

sender originates a message, sent, that can be perceived.

Dependency graph for sentence: Kim yelped. Token yelped is labeled SENDING-INIT and has an edge labeled sender to token Kim. Dependency graph for sentence: Kim and Sandy conversed. Token conversed is labeled SENDING-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 SENDING-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 SENDING-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 SENDING-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.

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: limit, limited

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.

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

experiencer experiences experienced. Can be used in a very general sense to label a non-core participant that are influenced by an eventuality, including beneficiaries and maleficiaries as well as impassive and even unconscious observers and “bystanders”. Especially used for sensory and mental perception as well as addressees in communication, often in combination with the MESSAGE and/or SENDING frame.

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 topic 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 topic to token adventure. Dependency graph for sentence: Kim talked to Sandy. Token talked is labeled SENDING-INIT and has an edge labeled sender to token Kim and an edge labeled EXPERIENCER to token Sandy. 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 EXPERIENCER 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 EXPERIENCER to token Kim and an edge labeled participant to token Sandy and an edge labeled scene to token spurn. 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.

(Croft 2002)

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.

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.

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: I was six years old. Token old is labeled AGE and has an edge labeled has-age to token I and an edge labeled QUANTITY to token years. 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 SENDING-INIT and has an edge labeled TIME to token hours.

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. Token ranked is labeled RANK and has an edge labeled has-rank to token Kim and an edge labeled rank to token second. 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: that would have given a much greater air of truth to my story. Token truth is labeled REALITY and has an edge labeled has-reality to token story. 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.

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 topic 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.

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.

META

Roles: participant, scene

A “meta” frame for control predicates where the participant dependent is assigned a role by the scene dependent. This role 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 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. Token going is labeled LOCATION-INIT and has an edge labeled has-location 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. Token going is labeled LOCATION-INIT and has an edge labeled has-location to token Sandy. Dependency graph for sentence: Kim plays tennis. Token plays is labeled META and has an edge labeled participant to token Kim. Token tennis is labeled SITUATION-DYN and has an edge labeled situee to token Kim. Dependency graph for sentence: Kim used to play tennis. Token used is labeled META-HABIT-TIME and has an edge labeled participant to token Kim. Token play is labeled META and has an edge labeled participant to token Kim. Token tennis is labeled SITUATION-DYN and has an edge labeled situee 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 to token Winston and an edge labeled scene to token prüfen. Token prüfen is labeled MESSAGE-INIT and has an edge labeled EXPERIENCER to token Winston and an edge labeled topic to token das.

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 to token Kim and an edge labeled surface 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 to token Kim and an edge labeled possessum 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 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 topic to token clown and an edge labeled EXPERIENCER to token I. Token smiled is labeled SENDING 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 norm 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: 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 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 to token devoted.

MESSAGE

Roles: topic, message

A message about topic with content message exists in perceived, measured, or recorded form. When a message is created through expression or observation, use MESSAGE-INIT. When message and topic are both realized, content must assign a role to topic. Combine with SENDER and EXPERIENCER.

Use MESSAGE for predicates of expression if there is a topic and/or message argument (otherwise, use SENDING):

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 message 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 message to token fine. Dependency graph for sentence: Kim called Sandy a liar. Token called is labeled MESSAGE-INIT and has an edge labeled SENDER to token Kim and an edge labeled topic to token Sandy and an edge labeled message to token liar. Token liar is labeled SENDING-HABIT and has an edge labeled sender to token Sandy. Dependency graph for sentence: Kim told Sandy a secret. Token told 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 message to token secret. Dependency graph for sentence: Kim talked about Sandy. Token talked is labeled MESSAGE-INIT and has an edge labeled SENDER to token Kim and an edge labeled topic to token Sandy. Dependency graph for sentence: Kim talked shit about Sandy. Token talked is labeled MESSAGE-INIT and has an edge labeled SENDER to token Kim and an edge labeled message to token shit and an edge labeled topic to token Sandy. Token shit is labeled MESSAGE and has an edge labeled topic to token Sandy.

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 message to token no.

What is depicted or talked/thought/etc. about gets the topic role:

Dependency graph for sentence: a picture of the heron. Token picture is labeled MESSAGE and has an edge labeled topic to token heron. Dependency graph for sentence: Kim drew the the heron. Token drew is labeled MESSAGE-INIT and has an edge labeled SENDER to token Kim and an edge labeled topic to token heron. Dependency graph for sentence: history book. Token book is labeled MESSAGE and has an edge labeled topic to token history. Dependency graph for sentence: a book about the primeval forest. Token book is labeled MESSAGE and has an edge labeled topic to token forest.

The result of recording something gets the message role:

Dependency graph for sentence: The concert was recorded on tape. Token recorded is labeled MESSAGE-INIT and has an edge labeled topic to token concert and an edge labeled MEDIUM to token tape. 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 message to token picture. Dependency graph for sentence: Kim wrote Sandy a letter. Token wrote 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 message to token letter. Dependency graph for sentence: Kim wrote the message onto a piece of paper with a pen in big red letters. Token wrote is labeled MESSAGE-INIT and has an edge labeled SENDER to token Kim and an edge labeled message to token message and an edge labeled MEDIUM to token paper and an edge labeled MEANS to token pen and an edge labeled ACCOMPANIER to token letters. Token letters is labeled ENTITY and has an edge labeled SAME to token message. Dependency graph for sentence: The band recorded an album. Token recorded is labeled MESSAGE-INIT and has an edge labeled SENDER to token band and an edge labeled message to token album.

Use MESSAGE for predicates of perception if there is a topic and/or message argument (otherwise, use EXPERIENCE):

Dependency graph for sentence: Kim saw a flower. Token saw is labeled MESSAGE and has an edge labeled EXPERIENCER to token Kim and an edge labeled topic to token flower. Dependency graph for sentence: Kim found the flower beautiful. Token found is labeled MESSAGE and has an edge labeled EXPERIENCER to token Kim and an edge labeled topic to token flower and an edge labeled message to token beautiful. Token beautiful is labeled PROPERTY and has an edge labeled has-property to token flower. Dependency graph for sentence: Kim thinks Sandy is a liar. Token thinks is labeled MESSAGE and has an edge labeled EXPERIENCER to token Kim and an edge labeled message to token liar. Dependency graph for sentence: Kim thinks Sandy a liar. Token thinks is labeled MESSAGE and has an edge labeled EXPERIENCER to token Kim and an edge labeled topic to token Sandy and an edge labeled message to token liar. Token liar is labeled SENDING-HABIT and has an edge labeled sender to token Sandy. Dependency graph for sentence: Kim saw Sandy swim. Token saw is labeled MESSAGE and has an edge labeled EXPERIENCER to token Kim and an edge labeled topic to token Sandy and an edge labeled message to token swim. Token swim is labeled LOCATION-DYN and has an edge labeled has-location to token Sandy.

Predicates that denote the initiation of perception (e.g., by acquiring knowledge, or observation, or reasoning, use MESSAGE-INIT):

Dependency graph for sentence: The Thought Police observed Windston. Token observed is labeled MESSAGE-INIT and has an edge labeled EXPERIENCER to token Police and an edge labeled topic to token Windston. Dependency graph for sentence: Kim studied linguistics. Token studied is labeled MESSAGE-INIT and has an edge labeled EXPERIENCER to token Kim and an edge labeled topic to token linguistics. Dependency graph for sentence: Kim noticed the bird. Token noticed is labeled MESSAGE-INIT and has an edge labeled EXPERIENCER to token Kim and an edge labeled topic to token bird. Dependency graph for sentence: Kim taught Sandy Spanish. Token taught 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 topic to token Spanish. Dependency graph for sentence: Kim measured the elasticity. Token measured is labeled MESSAGE-INIT and has an edge labeled EXPERIENCER to token Kim and an edge labeled topic to token elasticity. Dependency graph for sentence: The jury found Kim guilty of the crime. Token found is labeled MESSAGE-INIT and has an edge labeled EXPERIENCER to token jury and an edge labeled topic to token Kim and an edge labeled message to token guilty. Token guilty is labeled META and has an edge labeled participant to token Kim and an edge labeled scene to token crime. Token crime is labeled ENTITY and has an edge labeled CAUSER to token Kim.

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 message to token everything. Dependency graph for sentence: Kim forgot about Sandy. Token forgot is labeled MESSAGE-DEINIT and has an edge labeled EXPERIENCER to token Kim and an edge labeled topic to token Sandy.

EVALUATION

Roles: evaluee, evaluation

Special case of MESSAGE that involves a value judgment or emotion 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.

NORM

Roles: norm-topic, norm

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 NORM-INIT and has an edge labeled SENDER to token Kim and an edge labeled norm-topic to token Sandy and an edge labeled norm to token call. Token call is labeled SENDING and has an edge labeled sender to token Sandy. Dependency graph for sentence: sales target. Token target is labeled NORM and has an edge labeled norm-topic to token sales. Dependency graph for sentence: Kim wants to swim. Token wants is labeled NORM and has an edge labeled norm-topic to token Kim and an edge labeled norm 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 NORM and has an edge labeled EXPERIENCER to token Kim and an edge labeled norm-topic to token Sandy and an edge labeled norm to token swim. Token swim is labeled LOCATION-DYN and has an edge labeled has-location to token Sandy.

NONCOMP

Roles: has-noncomp, noncomp

Pseudoframe used to mark syntactic dependents that are part of a multiword predicate.

PERTINENCE

Roles: belongs, belongs-with

belongs belongs to or with belongs-with, typically in a vague sense. Use this only if none of the subframes really fit.

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.

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.

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 topic 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 SENDING 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 message to token something.

DYN

Roles: has-dyn, dyn

dyn is a dynamic process involving possibly multiple occurrences of has-dyn.

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.

CONTINUATION

Roles: continued, continuation

continuation is an event with continued as an initial subeventuality that continues throughout continuation.

DEINIT

Roles: deinitiated, deinitiation

deinitiation is an event with deinitiated as an initial subeventuality, acting towards the end of deinitiated.

HABIT

Roles: habitual, habit

habit is an event with habitual as a frequent or usual subeventuality.

INIT

Roles: initiated, initiation

initiation is an event acting towards the bringing about of initiated, with initiated as a possible final subeventuality.

PREVENTION

Roles: prevented, prevention

prevention is an event as part of which the eventuality prevented fails to come about.

TRANSIT

Roles: transitory, transition

transition is an event during which the eventuality transitory comes about and ends, possibly repeatedly.

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.

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 message 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.

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.

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 EXPERIENCER 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 SENDING-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.

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 topic 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 SENDING-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. 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.

Annotating Figurative Language

When a predicate is used in a figurative sense, you may optionally provide in addition the literal sense using the >> notation:

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.

References

Leon Stassen (1997). Intransitive Predication. Oxford University Press.

William Croft (2022). Morphosyntax: constructions of the world’s languages. Cambridge University Press.