aymaralima/verbenet

Verb∋Net 1.0.0

Verb∋Net is a lexicon of French verbs organised in the same way as the English VerbNet. Verbs are grouped into classes that share thematic roles (with selectional restrictions) and syntactic frames, and each frame has an example and a semantic formula.

• Website: https://aymara.github.io/verbenet/ (browse classes and verbs, format documentation)
• Source and issues: https://github.com/aymara/verbenet
• Paper: Adapting VerbNet to French using existing resources (LREC 2014)

This version has 229 classes, 97 subclasses, 525 frames and 4,177 verb–class pairs (2,827 distinct verbs).

Contents

The XML files in xml/ are the reference data, identical to the GitHub release. The two JSON Lines tables below are derived from them for convenience:

• frames: one row per frame. Inheritance is already resolved: roles includes roles inherited from parent classes (a subclass that restates a role replaces its restrictions), and members lists every verb the frame applies to, i.e. the members of the class that defines it and of all its subclasses.

  Field	Description
  class_id, top_class, parent_class	The (sub)class that defines the frame, its top-level class and its parent
  frame_index	Position of the frame in its class
  primary, syntax_description	The frame in constituent notation (NP V NP PP) and with roles (Agent V Theme)
  examples	French example sentence(s)
  syntax	Ordered constituents: element (NP, VERB, PREP, PSUBJ, VINF…), role, and attributes such as modifier, pronominal, introduced_by, prepositions
  semantics	Semantic formula, e.g. approve(during(E), Agent, Theme)
  roles	Thematic roles with their selectional restrictions
  members	Verbs the frame applies to
  lg_tables, lvf_classes	Linked Lexique-Grammaire tables and Les Verbes Français classes (inherited if not set)

• members: one row per (verb, class) pair: verb, class_id, top_class, parent_class, lg_tables, lvf_classes.

from datasets import load_dataset

frames = load_dataset("aymaralima/verbenet", "frames", split="train")
members = load_dataset("aymaralima/verbenet", "members", split="train")

The data is also available as a Python package: pip install verbenet.

Citation

@inproceedings{pradet-etal-2014-adapting,
    title = "Adapting {V}erb{N}et to {F}rench using existing resources",
    author = {Pradet, Quentin and Danlos, Laurence and de Chalendar, Ga{\"e}l},
    booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
    month = may,
    year = "2014",
    address = "Reykjavik, Iceland",
    publisher = "European Language Resources Association (ELRA)",
    pages = "1122--1126"
}

License

Creative Commons Attribution-ShareAlike 4.0 International.