Semantic Parsing for High-Precision Semantic Role Labelling

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Semantic Parsing for High-Precision Semantic Role Labelling

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by Paola Merlo , Gabriele Musillo

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BibTeX

@MISC{Merlo_semanticparsing,
    author = {Paola Merlo and Gabriele Musillo},
    title = {Semantic Parsing for High-Precision Semantic Role Labelling},
    year = {}
}

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Abstract

In this paper, we report experiments that explore learning of syntactic and semantic representations. First, we extend a state-of-the-art statistical parser to produce a richly annotated tree that identifies and labels nodes with semantic role labels as well as syntactic labels. Secondly, we explore rule-based and learning techniques to extract predicate-argument structures from this enriched output. The learning method is competitive with previous single-system proposals for semantic role labelling, yields the best reported precision, and produces a rich output. In combination with other high recall systems it yields an F-measure of 81%. 1

Keyphrases

high-precision semantic role state-of-the-art statistical parser semantic role labelling previous single-system proposal syntactic label high recall system label node rich output semantic representation semantic role label learning method predicate-argument structure reported precision

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