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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.