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Accurate Deep Syntactic Parsing of Graphs: The Case of French

Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)

DOI:10.63317/3qwi5kfcfpnu

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.

Details

Paper ID
lrec2016-main-566
Pages
pp. 3563-3568
BibKey
ribeyre-etal-2016-accurate
Editor
N/A
Publisher
European Language Resources Association (ELRA)
ISSN
2522-2686
ISBN
978-2-9517408-9-1
Conference
Tenth International Conference on Language Resources and Evaluation
Location
Portorož, Slovenia
Date
23 May 2016 28 May 2016

Authors

  • CR

    Corentin Ribeyre

  • EV

    Eric Villemonte de la Clergerie

  • DS

    Djamé Seddah

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