1997 DisambigOfProperNamesInText
- (WRC, 1997) ⇒ Nina Wacholder, Yael Ravin, Misook Choi. (1997). “Disambiguation of Proper Names in Text.” In: Proceedings of the fifth Conference on Applied Natural Language Processing, 1997.
Subject Headings: Named Entity Mention Resolution Algorithm, Named Entity Mention Detection.
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Abstract
- Identifying the occurrences of proper names in text and the entities they refer to can be a difficult task because of the manyto-many mapping between names and their referents. We analyze the types of ambiguity - structural and semantic - that make the discovery of proper names difficult in text, and describe the heuristics used to disambiguate names in Nominator, a fully-implemented module for proper name recognition developed at the IBM
1. Introduction
- The need to identify proper names has two aspects: the recognition of known names and the discovery of new names. Since obtaining and maintaining a name database requires significant effort, many applications need to operate in the absence of such a resource.
- A PP may be attached to the preceding NP and form part of a single large name, as in NP[Midwest Center PP[for NP[Computer Research]]). Alternatively it may be independent of the preceding NP, as in NP[Carnegie Hall] PP[for NP[Irwin Berlin]], where for separates two distinct names, Carnegie Hall and Irwin Berlin.
Conclusion
- In another sense, however, development of a module like Nominator still requires considerable human effort to discover reliable heuristics, particularly when only minimal information is used. These heuristics are somewhat domain dependent: different generalizations hold for names of drugs and chemicals than those identified for names of people or organizations. In addition, as the heuristics depend on linguistic conventions, they are language dependent, and need updating when stylistic conventions change. Note, for example, the recent popularity of software names which include exclamation points as part of the name. Because of these difficulties, we believe that for the forseeable future, practical applications to discover new names in text will continue to require the sort of human effort invested in Nominator.
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