Accurate Deep Syntactic Parsing of Graphs: The Case of French
Corentin Ribeyre, Eric Villemonte de la Clergerie, Djamé Seddah
Abstract
Parsing predicate-argument structures in a deep syntax framework requires graphs to be predicted. Argument structures represent a higher level of abstraction than the syntactic ones and are thus more difficult to predict even for highly accurate parsing models on surfacic syntax. In this paper we investigate deep syntax parsing, using a French data set (Ribeyre et al., 2014a). We demonstrate that the use of topologically different types of syntactic features, such as dependencies, tree fragments, spines or syntactic paths, brings a much needed context to the parser. Our higher-order parsing model, gaining thus up to 4 points, establishes the state of the art for parsing French deep syntactic structures.- Anthology ID:
- L16-1566
- Volume:
- Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
- Month:
- May
- Year:
- 2016
- Address:
- Portorož, Slovenia
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 3563–3568
- Language:
- URL:
- https://aclanthology.org/L16-1566
- DOI:
- Cite (ACL):
- Corentin Ribeyre, Eric Villemonte de la Clergerie, and Djamé Seddah. 2016. Accurate Deep Syntactic Parsing of Graphs: The Case of French. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 3563–3568, Portorož, Slovenia. European Language Resources Association (ELRA).
- Cite (Informal):
- Accurate Deep Syntactic Parsing of Graphs: The Case of French (Ribeyre et al., LREC 2016)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/L16-1566.pdf