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Experimental Support for a Categorical Compositional Distributional Model of Meaning

Abstract:

Modelling compositional meaning for sentences using empirical distributional methods has been a challenge for computational linguists. We implement the abstract categorical model of Coecke et al. (arXiv:1003.4394v1 [cs.CL]) using data from the BNC and evaluate it. The implementation is based on unsupervised learning of matrices for relational words and applying them to the vectors of their arguments. The evaluation is based on the word disambiguation task developed by Mitchell and Lapata (200...

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Publication status:
Published

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Authors


Grefenstette, E More by this author
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Institution:
University of Oxford
Department:
Oxford, MPLS, Computer Science
Journal:
Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing (2011)
Volume:
abs/1106.4058
Pages:
1394-1404
Publication date:
2011
URN:
uuid:71c9f5a4-ab18-4cbd-8a5e-279ddd64287b
Source identifiers:
305758
Local pid:
pubs:305758

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