Computer Laboratory

Diarmuid Ó Séaghdha

Modelling selectional preferences in a lexical hierarchy


Diarmuid Ó Séaghdha and Anna Korhonen

This paper describes Bayesian selectional preference models that incorporate knowledge from a lexical hierarchy such as WordNet. Inspired by previous work on modelling with WordNet, these approaches are based either on “cutting” the hierarchy at an appropriate level of generalisation or on a “walking” model that selects a path from the root to a leaf. In an evaluation comparing against human plausibility judgements, we show that the models presented here outperform previously proposed comparableWordNet-based models, are competitive with state-of-the-art selectional preference models and are particularly well suited to estimating plausibility for items that were not seen in training.

  author = 	 {Diarmuid {\'O S\'eaghdha} and Anna Korhonen},
  title = 	 Modelling selectional preferences in a lexical hierarchy},
  booktitle = 	 {Proceedings of the 1st Joint Conference on Lexical and Computational Semantics (*SEM)},
  year =	 2012,
  address =	 {Montreal, Canada}