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Blow the Dog Whistle: A Chinese Dataset for Cant Understanding with Common Sense and World Knowledge

2021-04-06 · NAACL 2021 4 · Canwen Xu, Wangchunshu Zhou, Tao Ge, Ke Xu, Julian McAuley, Furu Wei

Cant is important for understanding advertising, comedies and dog-whistle politics. However, computational research on cant is hindered by a lack of available datasets. In this paper, we propose a large and diverse Chinese dataset for creating and understanding cant from a computational linguistics perspective. We formulate a task for cant understanding and provide both quantitative and qualitative analysis for tested word embedding similarity and pretrained language models. Experiments suggest that such a task requires deep language understanding, common sense, and world knowledge and thus can be a good testbed for pretrained language models and help models perform better on other tasks. The code is available at https://github.com/JetRunner/dogwhistle. The data and leaderboard are available at https://competitions.codalab.org/competitions/30451.

📄 PDF Abstract BibTeX arXiv:2104.02704

Code (1)

JetRunner/dogwhistle 공식 구현 pytorch

Tasks

Common Sense ReasoningWorld Knowledge

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