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UGroningen: Negation detection with Discourse Representation Structures
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BibTeX
@MISC{Basile_ugroningen:negation,
author = {Valerio Basile and Johan Bos and Kilian Evang and Noortje Venhuizen},
title = {UGroningen: Negation detection with Discourse Representation Structures},
year = {}
}
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Abstract
We use the NLP toolchain that is used to construct the Groningen Meaning Bank to address the task of detecting negation cue and scope, as defined in the shared task “Resolving the Scope and Focus of Negation”. This toolchain applies the C&C tools for parsing, using the formalism of Combinatory Categorial Grammar, and applies Boxer to produce semantic representations in the form of Discourse Representation Structures (DRSs). For negation cue detection, the DRSs are converted to flat, non-recursive structures, called Discourse Representation Graphs (DRGs). DRGs simplify cue detection by means of edge labels representing relations. Scope detection is done by gathering the tokens that occur within the scope of a negated DRS. The result is a system that is fairly reliable for cue detection and scope detection. Furthermore, it provides a fairly robust algorithm for detecting the negated event or property within the scope. 1
Keyphrases
discourse representation structure negation detection scope detection cue detection edge label semantic representation groningen meaning bank nlp toolchain applies boxer robust algorithm discourse representation graph negated event negation cue non-recursive structure negation cue detection combinatory categorial grammar negated drs
