Modeling Violations of Selectional Restrictions with Distributional Semantics

Emmanuele Chersoni, Adrià Torrens Urrutia, Philippe Blache, Alessandro Lenci


Abstract
Distributional Semantic Models have been successfully used for modeling selectional preferences in a variety of scenarios, since distributional similarity naturally provides an estimate of the degree to which an argument satisfies the requirement of a given predicate. However, we argue that the performance of such models on rare verb-argument combinations has received relatively little attention: it is not clear whether they are able to distinguish the combinations that are simply atypical, or implausible, from the semantically anomalous ones, and in particular, they have never been tested on the task of modeling their differences in processing complexity. In this paper, we compare two different models of thematic fit by testing their ability of identifying violations of selectional restrictions in two datasets from the experimental studies.
Anthology ID:
W18-4603
Volume:
Proceedings of the Workshop on Linguistic Complexity and Natural Language Processing
Month:
August
Year:
2018
Address:
Santa Fe, New-Mexico
Venue:
WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
20–29
Language:
URL:
https://aclanthology.org/W18-4603
DOI:
Bibkey:
Cite (ACL):
Emmanuele Chersoni, Adrià Torrens Urrutia, Philippe Blache, and Alessandro Lenci. 2018. Modeling Violations of Selectional Restrictions with Distributional Semantics. In Proceedings of the Workshop on Linguistic Complexity and Natural Language Processing, pages 20–29, Santa Fe, New-Mexico. Association for Computational Linguistics.
Cite (Informal):
Modeling Violations of Selectional Restrictions with Distributional Semantics (Chersoni et al., 2018)
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PDF:
https://aclanthology.org/W18-4603.pdf