Paper: A Robust and Extensible Exemplar-Based Model of Thematic Fit

ACL ID E09-1094
Title A Robust and Extensible Exemplar-Based Model of Thematic Fit
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

This paper presents a new, exemplar-based model of thematic fit. In contrast to pre- vious models, it does not approximate thematic fit as argument plausibility or ‘fit with verb selectional preferences’, but directly as semantic role plausibility for a verb-argument pair, through similarity- based generalization from previously seen verb-argument pairs. This makes the model very robust for data sparsity. We argue that the model is easily extensible to a model of semantic role ambiguity reso- lution during online sentence comprehen- sion. The model is evaluated on human seman- tic role plausibility judgments. Its predic- tions correlate significantly with the hu- man judgments. It rivals two state-of-the- art models of thematic fit and exceeds their performance on previously unseen or ...