A tree kernel-based shallow semantic parser for thematic role extraction

Daniele Pighin; Alessandro Moschitti

A tree kernel-based shallow semantic parser for thematic role extraction

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We present a simple, two-steps supervised strategy for the identification and classification of thematic roles in natural language texts. We employ no external source of information but automatic parse trees of the input sentences. We use a few attribute-value features and tree kernel functions applied to specialized structured features. Different configurations of our thematic role labeling system took part in 2 tasks of the SemEval 2007 evaluation campaign, namely the closed tasks on semantic role labeling for the English and the Arabic languages. In this paper we present and discuss the system configuration that participated in the English semantic role labeling task and present new results obtained after the end of the evaluation campaign.

Original language	English
Title of host publication	AI IA 2007
Subtitle of host publication	Artificial Intelligence and Human-Oriented Computing - 10th Congress of the Italian Association for Artificial Intelligence, Proceedings
Pages	350-361
Number of pages	12
Publication status	Published - 1 Dec 2007
Event	10th Congress of the Italian Association for Artificial Intelligence, AI IA 2007 - Rome, Italy Duration: 10 Sep 2007 → 13 Sep 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4733 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	10th Congress of the Italian Association for Artificial Intelligence, AI IA 2007
Country	Italy
City	Rome
Period	10/9/07 → 13/9/07

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ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

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Pighin, D., & Moschitti, A. (2007). A tree kernel-based shallow semantic parser for thematic role extraction. In AI IA 2007: Artificial Intelligence and Human-Oriented Computing - 10th Congress of the Italian Association for Artificial Intelligence, Proceedings (pp. 350-361). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4733 LNAI).

A tree kernel-based shallow semantic parser for thematic role extraction. / Pighin, Daniele; Moschitti, Alessandro.

AI IA 2007: Artificial Intelligence and Human-Oriented Computing - 10th Congress of the Italian Association for Artificial Intelligence, Proceedings. 2007. p. 350-361 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4733 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Pighin, D & Moschitti, A 2007, A tree kernel-based shallow semantic parser for thematic role extraction. in AI IA 2007: Artificial Intelligence and Human-Oriented Computing - 10th Congress of the Italian Association for Artificial Intelligence, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4733 LNAI, pp. 350-361, 10th Congress of the Italian Association for Artificial Intelligence, AI IA 2007, Rome, Italy, 10/9/07.

Pighin D, Moschitti A. A tree kernel-based shallow semantic parser for thematic role extraction. In AI IA 2007: Artificial Intelligence and Human-Oriented Computing - 10th Congress of the Italian Association for Artificial Intelligence, Proceedings. 2007. p. 350-361. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

Pighin, Daniele ; Moschitti, Alessandro. / A tree kernel-based shallow semantic parser for thematic role extraction. AI IA 2007: Artificial Intelligence and Human-Oriented Computing - 10th Congress of the Italian Association for Artificial Intelligence, Proceedings. 2007. pp. 350-361 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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A tree kernel-based shallow semantic parser for thematic role extraction

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