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%.