Towards a Vector Space Model for FrameNet-like Resources

Marco Pennacchiotti, Diego De Cao, Paolo Marocco, Roberto Basili


Abstract
In this paper, we present an original framework to model frame semantic resources (namely, FrameNet) using minimal supervision. This framework can be leveraged both to expand an existing FrameNet with new knowledge, and to induce a FrameNet in a new language. Our hypothesis is that a frame semantic resource can be modeled and represented by a suitable semantic space model. The intuition is that semantic spaces are an effective model of the notion of “being characteristic of a frame” for both lexical elements and full sentences. The paper gives two main contributions. First, it shows that our hypothesis is valid and can be successfully implemented. Second, it explores different types of semantic VSMs, outlining which one is more suitable for representing a frame semantic resource. In the paper, VSMs are used for modeling the linguistic core of a frame, the lexical units. Indeed, if the hypothesis is verified for these units, the proposed framework has a much wider application.
Anthology ID:
L08-1202
Volume:
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)
Month:
May
Year:
2008
Address:
Marrakech, Morocco
Editors:
Nicoletta Calzolari, Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2008/pdf/202_paper.pdf
DOI:
Bibkey:
Cite (ACL):
Marco Pennacchiotti, Diego De Cao, Paolo Marocco, and Roberto Basili. 2008. Towards a Vector Space Model for FrameNet-like Resources. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08), Marrakech, Morocco. European Language Resources Association (ELRA).
Cite (Informal):
Towards a Vector Space Model for FrameNet-like Resources (Pennacchiotti et al., LREC 2008)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2008/pdf/202_paper.pdf