@inproceedings{ribeyre-etal-2016-accurate,
title = "Accurate Deep Syntactic Parsing of Graphs: The Case of {F}rench",
author = "Ribeyre, Corentin and
Villemonte de la Clergerie, Eric and
Seddah, Djam{\'e}",
booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC}'16)",
month = may,
year = "2016",
address = "Portoro{\v{z}}, Slovenia",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/L16-1566",
pages = "3563--3568",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Accurate Deep Syntactic Parsing of Graphs: The Case of French
%A Ribeyre, Corentin
%A Villemonte de la Clergerie, Eric
%A Seddah, Djamé
%S Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16)
%D 2016
%8 may
%I European Language Resources Association (ELRA)
%C Portorož, Slovenia
%F ribeyre-etal-2016-accurate
%X 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.
%U https://aclanthology.org/L16-1566
%P 3563-3568
Markdown (Informal)
[Accurate Deep Syntactic Parsing of Graphs: The Case of French](https://aclanthology.org/L16-1566) (Ribeyre et al., LREC 2016)
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).