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Latent Variable Models of Selectional Preference

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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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