印地语歧义专名识别的学习

R. Sinha
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引用次数: 3

摘要

歧义专有名称是指在文本中使用时也是有效的字典单词,具有自己的含义的名称。例如,在英语中,“Mr. bush”中的“bush”是一个专有名词,而在“a dense bush”中,它是一个词汇实体。印地语中几乎所有的专有名称都有含义,并在字典中找到条目。命名实体的识别在机器翻译、红外和其他一些NLP任务中得到了广泛的应用。虽然对印地语NER进行了大量的调查,但还没有专门研究歧义专有名词的工作,因为歧义专有名词更难处理。本文提出了一种识别印地语中歧义专有名称的方法,该方法使用基于规则的混合方法和基于统计CRF的机器学习,使用形态学和上下文特征。该方法的f得分为71.6%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Learning Recognition of Ambiguous Proper Names in Hindi
An ambiguous proper name is a name which is also a valid dictionary word with a meaning of its own when used in the text. For example in English, the word 'bush' in 'Mr. Bush' is a proper name whereas in 'a dense bush' it is a lexical entity. Almost all proper names in Hindi have a meaning and find an entry in the dictionary. Recognition of named entities finds wide application in MT, IR and several other NLP tasks. While there have been a number of investigations on Hindi NER in general, no work has been reported exclusively on ambiguous proper nouns which are more difficult to deal with. This paper presents a methodology for recognizing ambiguous proper names in Hindi using hybridization of a rule-base and statistical CRF based machine learning using morphological and context features. The methodology yields a F-score of 71.6%.
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