事件代词解析研究

Ning Zhang, Fang Kong, Peifeng Li
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引用次数: 2

摘要

事件回指消解在语篇分析中起着重要的作用。与一般的名词短语相比,代词本身所承载的信息很少,消解事件代词是一个比较困难的任务。本文提出了一种基于机器学习的事件代词解析框架。探讨了事件代词解析的各种特征,包括平面特征和结构特征。在OntoNotes语料库上的实验表明,平面特征和结构特征都能很好地完成该任务。
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Research of Event Pronoun Resolution
Event anaphora resolution plays an important role in discourse analysis. In comparison with general noun phrases, pronouns carry little information of themselves, resolving the event pronouns is a more difficult task. This paper proposes a machine learning-based framework for event pronoun resolution. All kinds of features, including both flat and structural features, are explored for event pronoun resolution. Experiments on OntoNotes corpus show that both flat and structural features are very effective for this task.
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