Using entity features to classify implicit discourse relations
Using entity features to classify implicit discourse relations
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发表时间：
2010-09
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通讯作者：
Annie Louis;A. Joshi;R. Prasad;A. Nenkova
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作者：
Annie Louis;A. Joshi;R. Prasad;A. Nenkova
我们报告的结果预测的意义上的隐性话语关系相邻的句子在文本中。我们的研究集中在语篇关系和相关句子中出现的指称表达的属性之间的关联。兴趣属性包括共指信息、语法角色、信息状态和指称表达的句法形式。基于这些特征预测隐含话语关系的意义比随机基线要好得多，并且几个最具鉴别力的特征符合语言直觉。然而，这些功能不执行以及传统上用于意义预测的词汇功能。
We report results on predicting the sense of implicit discourse relations between adjacent sentences in text. Our investigation concentrates on the association between discourse relations and properties of the referring expressions that appear in the related sentences. The properties of interest include coreference information, grammatical role, information status and syntactic form of referring expressions. Predicting the sense of implicit discourse relations based on these features is considerably better than a random baseline and several of the most discriminative features conform with linguistic intuitions. However, these features do not perform as well as lexical features traditionally used for sense prediction.