Latent Variable Models of Selectional Preference
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If you have a question about this talk, please contact Laura Rimell.
This paper describes the application of so-called “topic models” to
selectional preference induction. Three models related to Latent Dirichlet
Allocation, a proven method for modelling document-word co-occurrences,
are presented and evaluated on datasets of human plausibility judgements.
Compared to previously proposed techniques, these models perform very
competitively, especially for infrequent predicate-argument combinations
where they exceed the quality of Web-scale predictions while using
relatively little data.
This talk is part of the NLIP Seminar Series series.
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