Mixing WordNet, VerbNet and PropBank for studying verb relations

Maria Teresa Pazienza, Marco Pennacchiotti, Fabio Massimo Zanzotto


Abstract
In this paper we present a novel resource for studying the semantics of verb relations. The resource is created by mixing sense relational knowledge enclosed in WordNet, frame knowledge enclosed in VerbNet and corpus knowledge enclosed in PropBank. As a result, a set of about 1000 frame pairs is made available. A frame pair represents a pair of verbs in a peculiar semantic relation accompanied with specific information, such as: the syntactic-semantic frames of the two verbs, the mapping among their thematic roles and a set of textual examples extracted from the PennTreeBank. We specifically focus on four relations: Troponymy, Causation, Entailment and Antonymy. The different steps required for the mapping are described in detail and statistics on resource mutual coverage are reported. We also propose a practical use of the resource for the task of Textual Entailment acquisition and for Question Answering. A first attempt for automate the mapping among verb arguments is also presented: early experiments show that simple techniques can achieve good results, up to 85% F-Measure.
Anthology ID:
L06-1223
Volume:
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
Month:
May
Year:
2006
Address:
Genoa, Italy
Editors:
Nicoletta Calzolari, Khalid Choukri, Aldo Gangemi, Bente Maegaard, Joseph Mariani, Jan Odijk, Daniel Tapias
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
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Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2006/pdf/379_pdf.pdf
DOI:
Bibkey:
Cite (ACL):
Maria Teresa Pazienza, Marco Pennacchiotti, and Fabio Massimo Zanzotto. 2006. Mixing WordNet, VerbNet and PropBank for studying verb relations. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06), Genoa, Italy. European Language Resources Association (ELRA).
Cite (Informal):
Mixing WordNet, VerbNet and PropBank for studying verb relations (Pazienza et al., LREC 2006)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2006/pdf/379_pdf.pdf