该文在基于特征的英文代词指代消解平台上,使用复合核函数,研究指代消解中待消解项“it”的识别问题。围绕“it”是否是待消解项,该文采取有效策略获得“it”句法结构信息与平面特征信息,并将它们结合起来生成“it”待消解项分类器。在测试分类器性能的同时,将其运用到代词指代消解中以检验它对指代消解的作用。最后在ACE2003基准语料上实验表明采用复合核生成的分类器具有较高的准确率,并能显著提高代词指代消解性能。
Abstract
This paper presents an automatic approach using Composite Kernel of SVM to determining whether “it” in text refers to a preceding noun phrase or is instead non-referential in the platform of feature-based English pronoun coreference resolution. We extract structure information and plane feature information about "it" in order to construct an anaphoricity filter. We examine the performance of the filter by introducing it into the pronoun coreference resolution task. Evaluation on the ACE2003 benchmark corpus shows that the filter achieves the highest performance by using Composite Kernel and the pronoun coreference resolution is improved by employing the filter.
Key wordsanaphoricity determination; composite kernel; coreference resolution
关键词
待消解项识别 /
复合核 /
指代消解
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Key words
anaphoricity determination /
composite kernel /
coreference resolution
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参考文献
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脚注
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基金
国家自然科学基金资助项目(60673041);高等学校博士学科点专项科研基金资助项目(200802850006);江苏省高校自然科学重大基础研究项目(08KJA520002);江苏省高校自然科学基础研究项目(08KJD520010);苏州市软件专项资助项目(SGR0807)
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