The Influence of Context on Sentence Acceptability Judgements

Jean-Philippe Bernardy, Shalom Lappin, Jey Han Lau

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Abstract
We investigate the influence that document context exerts on human acceptability judgements for English sentences, via two sets of experiments. The first compares ratings for sentences presented on their own with ratings for the same set of sentences given in their document contexts. The second assesses the accuracy with which two types of neural models — one that incorporates context during training and one that does not — predict these judgements. Our results indicate that: (1) context improves acceptability ratings for ill-formed sentences, but also reduces them for well-formed sentences; and (2) context helps unsupervised systems to model acceptability.
Anthology ID:
P18-2073
Volume:
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Month:
July
Year:
2018
Address:
Melbourne, Australia
Editors:
Iryna Gurevych, Yusuke Miyao
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
456–461
Language:
URL:
https://aclanthology.org/P18-2073
DOI:
10.18653/v1/P18-2073
Bibkey:
Cite (ACL):
Jean-Philippe Bernardy, Shalom Lappin, and Jey Han Lau. 2018. The Influence of Context on Sentence Acceptability Judgements. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 456–461, Melbourne, Australia. Association for Computational Linguistics.
Cite (Informal):
The Influence of Context on Sentence Acceptability Judgements (Bernardy et al., ACL 2018)
Copy Citation:
PDF:
https://preview.aclanthology.org/teach-a-man-to-fish/P18-2073.pdf
Note:
 P18-2073.Notes.pdf
Presentation:
 P18-2073.Presentation.pdf
Video:
 https://preview.aclanthology.org/teach-a-man-to-fish/P18-2073.mp4
Code
 GU-CLASP/BLL2018