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首页> 外文会议>The 2008 IEEE International Conference on Natural Language Processing and Knowledge Engineering（IEEE NLP-KE 2008）(2008IEEE自然语言处理与知识工程国际会议)论文集 >Word Sense Disambiguation of the English Modal Verb May by Back Propagation Neural Network
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Word Sense Disambiguation of the English Modal Verb May by Back Propagation Neural Network

机译：反向传播神经网络可以消除英语情态动词的词义歧义

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摘要

This paper studies the word sense disambiguation of English modal verb “may”. Based on the analysis of the sense, category of modality and function of “may” in different contexts in the training corpus, a model of back propagation neural network for word sense disambiguation of “may” is established. It takes the mutual information of epistemic and non-epistemic “may” and the verb before and after “may” as well as active and passive voice of the sentence as the input vectors. The test to the model shows that the rate for correct disambiguation reaches 78%. This study extends the word sense disambiguation into the level of modality which is a breakthrough in both WSD and linguistic studies.
机译：本文研究了英语情态动词“ may”的词义歧义消除。基于对训练语料库中不同语境中“可能”的意义，模态种类和功能的分析，建立了一种用于“可能”词义消歧的反向传播神经网络模型。它以认知和非认知的“可能”以及“可能”之前和之后的动词以及句子的主动和被动语音的相互信息作为输入向量。对模型的测试表明正确消除歧义的比率达到了78％。这项研究将单词歧义消除扩展到情态水平，这在WSD和语言学研究中都是一个突破。

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