Bram Vandekerckhove
ABSTRACT
This paper presents a new, exemplar-based model of thematic fit. In contrast to previous 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 resolution during online sentence comprehension.
The model is evaluated on human semantic role plausibility judgments. Its predictions correlate significantly with the human judgments. It rivals two state-of-the-art models of thematic fit and exceeds their performance on previously unseen or low-frequency items.
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Index Terms
- A robust and extensible exemplar-based model of thematic fit
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