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A Distant Supervision Approach to Semantic Role Labeling

På svenska

Author

Summary, in English

Semanticrolelabelinghasbecomeakeymodule for many language processing applications such as question answering, information extraction, sentiment analysis, and machine translation. To build an unrestricted semantic role labeler, the first step is to develop a comprehensive proposition bank. However, creating such a bank is a costly enterprise, which has only been achieved for a handful of languages. In this paper, we describe a technique to build proposition banks for new languages using distant supervision. Starting from PropBank inEnglishandlooselyparallelcorporasuchas versions of Wikipedia in different languages, we carried out a mapping of semantic propositions we extracted from English to syntactic structures in Swedish using named entities. We trained a semantic parser on the generated Swedishpropositionsandwereporttheresults we obtained. Using the CoNLL 2009 evaluation script, we could reach the scores of 52.25 for labeled propositions and 62.44 for the unlabeled ones. We believe our approach can be appliedtotrainsemanticrolelabelersforother resource-scarce languages.

Publishing year

2015

Language

English

Pages

239-248

Publication/Series

Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics (*SEM 2015)

Document type

Conference paper

Topic

  • Computer Science

Conference name

Fourth Joint Conference on Lexical and Computational Semantics (*SEM 2015)

Conference date

2015-06-04 - 2015-06-07

Status

Published

ISBN/ISSN/Other

  • ISBN: 978-1-941643-39-6