Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/42051
Title: Improving noun phrase coreference resolution by matching strings
Authors: Yang, X. 
Zhou, G.
Su, J.
Tan, C.L. 
Issue Date: 2005
Source: Yang, X.,Zhou, G.,Su, J.,Tan, C.L. (2005). Improving noun phrase coreference resolution by matching strings. Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) 3248 : 22-31. ScholarBank@NUS Repository.
Abstract: In this paper we present a noun phrase coreference resolution system which aims to enhance the identification of the coreference realized by string matching. For this purpose, we make two extensions to the standard learn-ingbased resolution framework. First, to improve the recall rate, we introduce an additional set of features to capture the different matching patterns between noun phrases. Second, to improve the precision, we modify the instance selection strategy to allow non-anaphors to be included during training instance generation. The evaluation done on MEDLINE data set shows that the combination of the two extensions provides significant gains in the F-measure. © Springer-Verlag Berlin Heidelberg 2005.
Source Title: Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
URI: http://scholarbank.nus.edu.sg/handle/10635/42051
ISSN: 03029743
Appears in Collections:Staff Publications

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