Abstract
We present a cognitive model of inducing verb selectional preferences from individual verb usages. The selectional preferences for each verb argument are represented as a probability distribution over the set of semantic properties that the argument can possess—a semantic profile. The semantic profiles yield verb-specific conceptualizations of the arguments associated with a syntactic position. The proposed model can learn appropriate verb profiles from a small set of noisy training data, and can use them in simulating human plausibility judgments and analyzing implicit object alternation.
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Notes
- 1.
This paper is an updated and extended version of preliminary work on this approach presented in [2].
- 2.
- 3.
We do not remove alternate spellings of a term in WordNet; this will be seen in the profiles in the results section.
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Alishahi, A., Stevenson, S. (2013). Gradual Acquisition of Verb Selectional Preferences in a Bayesian Model. In: Villavicencio, A., Poibeau, T., Korhonen, A., Alishahi, A. (eds) Cognitive Aspects of Computational Language Acquisition. Theory and Applications of Natural Language Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31863-4_11
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