Abstract
In theoretical linguistics, logical metonymy is defined as the combination of an event-subcategorizing verb with an entity-denoting direct object (e.g., The author began the book), so that the interpretation of the VP requires the retrieval of a covert event (e.g., writing). Psycholinguistic studies have revealed extra processing costs for logical metonymy, a phenomenon generally explained with the introduction of new semantic structure. In this paper, we present a general distributional model for sentence comprehension inspired by the Memory, Unification and Control model by Hagoort (2013,2016). We show that our distributional framework can account for the extra processing costs of logical metonymy and can identify the covert event in a classification task.- Anthology ID:
- S17-1021
- Volume:
- Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017)
- Month:
- August
- Year:
- 2017
- Address:
- Vancouver, Canada
- Venue:
- *SEM
- SIGs:
- SIGSEM | SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 168–177
- Language:
- URL:
- https://aclanthology.org/S17-1021
- DOI:
- 10.18653/v1/S17-1021
- Cite (ACL):
- Emmanuele Chersoni, Alessandro Lenci, and Philippe Blache. 2017. Logical Metonymy in a Distributional Model of Sentence Comprehension. In Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017), pages 168–177, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Logical Metonymy in a Distributional Model of Sentence Comprehension (Chersoni et al., *SEM 2017)
- PDF:
- https://preview.aclanthology.org/starsem-semeval-split/S17-1021.pdf