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
- 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
- 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)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/P18-2073.pdf
- Code
- GU-CLASP/BLL2018