Fixed That for You: Generating Contrastive Claims with Semantic Edits

Conference · 02 June 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

DOI:https://doi.org/10.18653/v1/n19-1174· OSTI ID:2281906

Hidey, Christopher ^[1]; McKeown, Kathy ^[1]

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1. Columbia Univ., New York, NY (United States)

Understanding contrastive opinions is a key component of argument generation. Central to an argument is the claim, a statement that is in dispute. Generating a counter-argument then requires generating a response in contrast to the main claim of the original argument. To generate contrastive claims, we create a corpus of Reddit comment pairs self-labeled by posters using the acronym FTFY (fixed that for you). We then train neural models on these pairs to edit the original claim and produce a new claim with a different view. We demonstrate significant improvement over a sequence-to-sequence baseline in BLEU score and a human evaluation for fluency, coherence, and contrast.

• Research Organization: Columbia Univ., New York, NY (United States)
• Sponsoring Organization: USDOE Office of Inspector General (IG); USDOE Office of Energy Efficiency and Renewable Energy (EERE)
• DOE Contract Number: EE0007684
• OSTI ID: 2281906
• Journal Information: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Vol. 1; Conference: 17. Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2019), Minneapolis, MN (United States), 2-7 Jun 2019
• Country of Publication: United States
• Language: English