Language Models Use Monotonicity to Assess NPI Licensing

• URL: http://arxiv.org/abs/2105.13818v1
• Date: Fri, 28 May 2021 13:32:00 GMT
• Title: Language Models Use Monotonicity to Assess NPI Licensing
• Authors: Jaap Jumelet, Milica Deni\'c, Jakub Szymanik, Dieuwke Hupkes, Shane Steinert-Threlkeld
• Abstract summary: We investigate the semantic knowledge of language models (LMs) We focus on whether these LMs create categories of linguistic environments based on their semantic monotonicity properties, and whether these categories play a similar role in LMs as in human language understanding.
• Score: 8.856422030608188
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We investigate the semantic knowledge of language models (LMs), focusing on (1) whether these LMs create categories of linguistic environments based on their semantic monotonicity properties, and (2) whether these categories play a similar role in LMs as in human language understanding, using negative polarity item licensing as a case study. We introduce a series of experiments consisting of probing with diagnostic classifiers (DCs), linguistic acceptability tasks, as well as a novel DC ranking method that tightly connects the probing results to the inner workings of the LM. By applying our experimental pipeline to LMs trained on various filtered corpora, we are able to gain stronger insights into the semantic generalizations that are acquired by these models.

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