Building Textual Entailment Specialized Data Sets: a Methodology for Isolating Linguistic Phenomena Relevant to Inference

Luisa Bentivogli, Elena Cabrio, Ido Dagan, Danilo Giampiccolo, Medea Lo Leggio, Bernardo Magnini


Abstract
This paper proposes a methodology for the creation of specialized data sets for Textual Entailment, made of monothematic Text-Hypothesis pairs (i.e. pairs in which only one linguistic phenomenon relevant to the entailment relation is highlighted and isolated). The expected benefits derive from the intuition that investigating the linguistic phenomena separately, i.e. decomposing the complexity of the TE problem, would yield an improvement in the development of specific strategies to cope with them. The annotation procedure assumes that humans have knowledge about the linguistic phenomena relevant to inference, and a classification of such phenomena both into fine grained and macro categories is suggested. We experimented with the proposed methodology over a sample of pairs taken from the RTE-5 data set, and investigated critical issues arising when entailment, contradiction or unknown pairs are considered. The result is a new resource, which can be profitably used both to advance the comprehension of the linguistic phenomena relevant to entailment judgments and to make a first step towards the creation of large-scale specialized data sets.
Anthology ID:
L10-1331
Volume:
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)
Month:
May
Year:
2010
Address:
Valletta, Malta
Editors:
Nicoletta Calzolari, Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Mike Rosner, Daniel Tapias
Venue:
LREC
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Publisher:
European Language Resources Association (ELRA)
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URL:
http://www.lrec-conf.org/proceedings/lrec2010/pdf/478_Paper.pdf
DOI:
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Cite (ACL):
Luisa Bentivogli, Elena Cabrio, Ido Dagan, Danilo Giampiccolo, Medea Lo Leggio, and Bernardo Magnini. 2010. Building Textual Entailment Specialized Data Sets: a Methodology for Isolating Linguistic Phenomena Relevant to Inference. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), Valletta, Malta. European Language Resources Association (ELRA).
Cite (Informal):
Building Textual Entailment Specialized Data Sets: a Methodology for Isolating Linguistic Phenomena Relevant to Inference (Bentivogli et al., LREC 2010)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2010/pdf/478_Paper.pdf