Actions

Actions (or more fully, Action types) represent individual semantically disambiguated verbs.

Three valencies: Entity type valency, grammatical valency, and semantic valency

Actions acquire three kinds of valencies per any actant slot (subject, object 1, object 2 –2; the data model is potentially extensible further, beyond trivalent verbs):

1. entity type valency,valency, which defines which entity type is allowed in the given actant slot;
2. grammaticalmorphosyntactic valency,valency,  which is a free text field defining the prepositions,prepositions and grammatical cases, etc.but –uses ita formalized notation (grammatical cases are noted with numbers 1-6, prepositions are in quote marks "", alternative is usefulmarked forwith thea usepipe of our Actions for machine understanding;"|"); and
3. semantic valency,valency, i.e. what kind of role any the holderentity ofoccupying the given actant slot canhas acquireby implication (e.g., in our example, the subject of the Action “to travel” would have the semantic valency C “traveller”, and thus, in a research-oriented data projection, Alice could be tagged as traveller, and we could find all travellers throughout the dataset)).

ValenciesThe main benefits from valencies are that they:

1. guide coders in their choice of the correct Action (or towards creating a new one if none among the existing yet fits the syntactic and semantic definition).;
They also
2. allow us to implement data validation features in a data collection interface.interface;
Finally,
3. facilitate theymachine areunderstanding usefulof fortext, NLPallowing semantic disambiguation of different verbs based on their grammaticalmorphosyntactic valency,valency (recognized throughby dependency parsing,parsing), and optionally theiroptionally, entity type valency,valency (recognized e.g. through some other procedure (such asthrough named entity recognition).