tailieunhanh - Báo cáo khoa học: "Robust pronoun resolution with limited knowledge"

Most traditional approaches to anaphora resolution rely heavily on linguistic and domain knowledge. One of the disadvantages of developing a knowledgebased system, however, is that it is a very labourintensive and time-consuming task. This paper presents a robust, knowledge-poor approach to resolving pronouns in technical manuals, which operates on texts pre-processed by a part-of-speech tagger. | Robust pronoun resolution with limited knowledge Ruslan Mitkov School of Languages and European Studies University of Wolverhampton Stafford Street Wolverhampton WV1 1SB United Kingdom Abstract Most traditional approaches to anaphora resolution rely heavily on linguistic and domain knowledge. One of the disadvantages of developing a knowledgebased system however is that it is a very labour-intensive and time-consuming task. This paper presents a robust knowledge-poor approach to resolving pronouns in technical manuals which operates on texts pre-processed by a part-of-speech tagger. Input is checked against agreement and for a number of antecedent indicators. Candidates are assigned scores by each indicator and the candidate with the highest score is returned as the antecedent. Evaluation reports a success rate of which is better than the success rates of the approaches selected for comparison and tested on the same data. In addition preliminary experiments show that the approach can be successfully adapted for other languages with minimum modifications. 1. Introduction For the most part anaphora resolution has focused on traditional linguistic methods Carbonell Brown 1988 Carter 1987 Hobbs 1978 Ingria Stallard 1989 Lappin McCord 1990 Lappin Leass 1994 Mitkov 1994 Rich LuperFoy 1988 Sidner 1979 Webber 1979 . However to represent and manipulate the various types of linguistic and domain knowledge involved requires considerable human input and computational expense. While various alternatives have been proposed making use of . neural networks a situation semantics framework or the principles of reasoning with uncertainty . Connoly et al. 1994 Mitkov 1995 Tin Akman 1995 there is still a strong need for the development of robust and effective strategies to meet the demands of practical NLP systems and to enhance further the automatic processing of growing language resources. Several proposals have already addressed the anaphora resolution