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The Research on Chinese Coreference Resolution Based on Maximum Entropy Model and Rules

机译:基于最大熵模型和规则的中文共指解析度研究

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Coreference resolution is an important research topic in natural language processing, including the coreference resolution of proper nouns, common nouns and pronouns. In this paper, a coreference resolution algorithm of the Chinese noun phrase and the pronoun is proposed that based on maximum entropy model and rules. The use of maximum entropy model can integrate effectively a variety of separate features, on this basis to use rules method to improve the recall rate of digestion, and then use filtering rules to remove "noise" to further improve the accuracy rate of digestion. Experiments show that the F value of the algorithm in a closed test and an open test can reach 85.2% and 76.2% respectively, which improve about 12.9 percentage points and 7.8 percentage points compare with the method of rules respectively.
机译:共指解析是自然语言处理中的重要研究课题,包括专有名词,普通名词和代词的共指解析。本文提出了一种基于最大熵模型和规则的汉语名词短语与代词共指分解算法。利用最大熵模型可以有效地整合各种独立的特征,在此基础上使用规则方法提高消化的召回率,然后使用过滤规则去除“噪声”以进一步提高消化的准确率。实验表明,该算法在封闭测试和开放测试中的F值分别达到85.2%和76.2%,分别比规则方法提高了约12.9个百分点和7.8个百分点。

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