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Assessing Polyseme Sense Similarity through Co-predication Acceptability and Contextualised Embedding Distance

机译:通过共同预测可接受性和语境化嵌入距离评估多电晕感应相似性

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Co-predication is one of the most frequently used linguistic tests to tell apart shifts in po-lysemic sense from changes in homonymic meaning. It is increasingly coming under criticism as evidence is accumulating that it tends to mis-classify specific cases of polysemic sense alteration as homonymy. In this paper, we collect empirical data to investigate these accusations. We asses how co-predication acceptability relates to explicit ratings of polyseme word sense similarity, and how well either measure can be predicted through the distance between target words' contextualised word embeddings. We find that sense similarity appears to be a major contributor in determining co-predication acceptability, but that co-predication judgements tend to rate less similar sense interpretations as being as unacceptable as homonym pairs, effectively mis-classifying these instances. The tested contextualised word embeddings fail to predict word sense similarity consistently, but the similarities between BERT embeddings show a significant correlation with co-predication ratings. We take this finding as evidence that BERT embeddings might be better representations of context than encodings of word meaning.
机译:共同预测是最常用的语言试验之一,以便在同音鸣含义的变化中讲述Po-rysex意义上的变化。越来越多地受到批评,因为证据积累了它倾向于将特定案件分类为同名单的宣传。在本文中,我们收集了实证数据来调查这些指控。我们判断共同预测可接受性如何涉及多大级别词语感觉相似性的明确评级,并且可以通过目标单词的上下文化词嵌入之间的距离来预测尺寸的程度。我们发现感觉相似度似乎是确定共同预测可接受性时的主要贡献者,但是,共同预测判断倾向于将相似的意义解释与阳记相对一样不可接受,有效地分类这些实例。测试的上下文化词嵌入式未能始终如一地预测词感测相似性,但BERT EMBEDDINGS之间的相似性显示与共同预测额定值的显着相关性。我们认为这一发现作为BERT EMBEDDINGS的证据可能是更好的上下文表示而不是词含义的编码。

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