An Analysis of Natural Language Inference Benchmarks through the Lens of Negation
An Analysis of Natural Language Inference Benchmarks through the Lens of Negation
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DOI：
10.18653/v1/2020.emnlp-main.732
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发表时间：
2020-11
期刊：
影响因子：
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通讯作者：
Md Mosharaf Hossain;Venelin Kovatchev;Pranoy Dutta;T. Kao;Elizabeth Wei;Eduardo Blanco
中科院分区：
文献类型：
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作者：
Md Mosharaf Hossain;Venelin Kovatchev;Pranoy Dutta;T. Kao;Elizabeth Wei;Eduardo Blanco
否定在现有的自然语言推理基准中代表性不足。此外，人们通常可以忽略现有基准中的少数否定，仍然可以做出正确的推理判断。在本文中，我们提出了一个新的基准自然语言推理中，否定起着至关重要的作用。我们还表明，国家的最先进的变压器的斗争作出推断的判断与新的对。
Negation is underrepresented in existing natural language inference benchmarks. Additionally, one can often ignore the few negations in existing benchmarks and still make the right inference judgments. In this paper, we present a new benchmark for natural language inference in which negation plays a critical role. We also show that state-of-the-art transformers struggle making inference judgments with the new pairs.