Because Syntax does Matter: Improving Predicate-Argument Structures Parsing Using Syntactic Features - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2015

Because Syntax does Matter: Improving Predicate-Argument Structures Parsing Using Syntactic Features

Abstract

Parsing full-fledged predicate-argument structures in a deep syntax framework requires graphs to be predicted. Using the DeepBank (Flickinger et al., 2012) and the Predicate-Argument Structure treebank (Miyao and Tsujii, 2005) as a test field, we show how transition-based parsers, extended to handle connected graphs, benefit from the use of topologically different syntactic features such as dependencies, tree fragments, spines or syntactic paths, bringing a much needed context to the parsing models, improving notably over long distance dependencies and elided coordinate structures. By confirming this positive impact on an accurate 2nd-order graph-based parser (Martins and Almeida, 2014), we establish a new state-of-the-art on these data sets.
Fichier principal
Vignette du fichier
naaclhlt2015.pdf (233.85 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01174533 , version 1 (10-07-2015)

Licence

Attribution - NonCommercial - NoDerivatives

Identifiers

  • HAL Id : hal-01174533 , version 1

Cite

Corentin Ribeyre, Éric Villemonte de La Clergerie, Djamé Seddah. Because Syntax does Matter: Improving Predicate-Argument Structures Parsing Using Syntactic Features. Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Jun 2015, Denver, USA, United States. ⟨hal-01174533⟩
979 View
243 Download

Share

Gmail Facebook X LinkedIn More