In this paper, we discuss the human thematic fit judgement correlation task in the context of real-valued vector space word representations. Thematic fit is the extent to which an argument fulfils the selectional preference of a verb given a role: For example, how well "cake" fulfils the patient role of "cut". In recent work, systems have been evaluated on this task by finding the correlations of their output judgements with human-collected judgement data. This task is a representationindependent way of evaluating models that can be applied whenever a system score can be generated, and it is applicable wherever predicate-argument relations are significant to performance in end-user tasks. Significant progress has been made on this cognitive modeling task, leaving considerable space for future, more comprehensive types of evaluation.
CITATION STYLE
Sayeed, A., Greenberg, C., & Demberg, V. (2016). Thematic fit evaluation: An aspect of selectional preferences. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 99–105). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w16-2518
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