Detecting Asymmetric Semantic Relations in Context: A Case-Study on Hypernymy Detection

Yogarshi Vyas, Marine Carpuat
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引用次数: 8

Abstract

We introduce WHiC, a challenging testbed for detecting hypernymy, an asymmetric relation between words. While previous work has focused on detecting hypernymy between word types, we ground the meaning of words in specific contexts drawn from WordNet examples, and require predictions to be sensitive to changes in contexts. WHiC lets us analyze complementary properties of two approaches of inducing vector representations of word meaning in context. We show that such contextualized word representations also improve detection of a wider range of semantic relations in context.
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语境中不对称语义关系的检测:一个词的检测案例
我们介绍了WHiC,一个具有挑战性的测试平台,用于检测词之间的不对称关系。虽然以前的工作主要集中在检测词类型之间的超音,但我们从WordNet示例中提取特定上下文中的词的含义,并要求预测对上下文的变化敏感。这让我们分析两种方法的互补性诱导向量表示的词义在上下文中。我们表明,这种语境化的词表示也提高了对语境中更广泛的语义关系的检测。
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