It's not a Non-Issue: Negation as a Source of Error in Machine Translation

October 12, 2020 · Entered Twilight · 🏛 Findings

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Repo contents: README.md, chrF_pp.py, cue_detection_mt.py, data, env-setup, extract_negation.py, map.py, neg_error_annotations, negation_cue, output, ranking.py, results.py

Authors Md Mosharaf Hossain, Antonios Anastasopoulos, Eduardo Blanco, Alexis Palmer arXiv ID 2010.05432 Category cs.CL: Computation & Language Cross-listed cs.AI Citations 31 Venue Findings Repository https://github.com/mosharafhossain/negation-mt ⭐ 4 Last Checked 4 months ago

Abstract

As machine translation (MT) systems progress at a rapid pace, questions of their adequacy linger. In this study we focus on negation, a universal, core property of human language that significantly affects the semantics of an utterance. We investigate whether translating negation is an issue for modern MT systems using 17 translation directions as test bed. Through thorough analysis, we find that indeed the presence of negation can significantly impact downstream quality, in some cases resulting in quality reductions of more than 60%. We also provide a linguistically motivated analysis that directly explains the majority of our findings. We release our annotations and code to replicate our analysis here: https://github.com/mosharafhossain/negation-mt.