The Influence of Context on Sentence Acceptability Judgements
Jean-Philippe Bernardy, Shalom Lappin, Jey Han Lau, I Gurevych (ed.), Y Miyao (ed.)
ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers) | ASSOC COMPUTATIONAL LINGUISTICS-ACL | Published : 2018
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.
Awarded by Swedish Research Council
The research of the first two authors was supported by grant 2014-39 from the Swedish Research Council, which funds the Centre for Linguistic Theory and Studies in Probability in FLoV at the University of Gothenburg.