Aspectuality Across Genre: A Distributional Semantics Approach

Thomas Kober, Malihe Alikhani, Matthew Stone, Mark Steedman


Abstract
The interpretation of the lexical aspect of verbs in English plays a crucial role in tasks such as recognizing textual entailment and learning discourse-level inferences. We show that two elementary dimensions of aspectual class, states vs. events, and telic vs. atelic events, can be modelled effectively with distributional semantics. We find that a verb’s local context is most indicative of its aspectual class, and we demonstrate that closed class words tend to be stronger discriminating contexts than content words. Our approach outperforms previous work on three datasets. Further, we present a new dataset of human-human conversations annotated with lexical aspects and present experiments that show the correlation of telicity with genre and discourse goals.
Anthology ID:
2020.coling-main.401
Volume:
Proceedings of the 28th International Conference on Computational Linguistics
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
4546–4562
Language:
URL:
https://www.aclweb.org/anthology/2020.coling-main.401
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.coling-main.401.pdf