Some of Them Can be Guessed! Exploring the Effect of Linguistic Context in Predicting Quantifiers

June 01, 2018 ยท Declared Dead ยท ๐Ÿ› Annual Meeting of the Association for Computational Linguistics

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Authors Sandro Pezzelle, Shane Steinert-Threlkeld, Raffaela Bernardi, Jakub Szymanik arXiv ID 1806.00354 Category cs.CL: Computation & Language Cross-listed cs.AI Citations 5 Venue Annual Meeting of the Association for Computational Linguistics Last Checked 4 months ago
Abstract
We study the role of linguistic context in predicting quantifiers (`few', `all'). We collect crowdsourced data from human participants and test various models in a local (single-sentence) and a global context (multi-sentence) condition. Models significantly out-perform humans in the former setting and are only slightly better in the latter. While human performance improves with more linguistic context (especially on proportional quantifiers), model performance suffers. Models are very effective in exploiting lexical and morpho-syntactic patterns; humans are better at genuinely understanding the meaning of the (global) context.
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