基于中心理论和话语结构的交互式问答文本指代消解

与传统新闻文本相比,交互式问答中蕴含着更为丰富的语言现象。在传统的针对新闻文本的指代消解方案的基础上,融入了交互式问答特有的特征集,给出了一个适于交互式问答文本的指代消解方案。具体而言,基于浅层语义角色分析的结果进行话语结构的识别,根据识别出的话语结构进行话语中心及中心跳转的识别。将获取到的话语中心及跳转信息组织成交互式文本特有的特征集,使用交互式问答领域广泛使用的TREC2004和TREC2007的评测语料进行指代消解的实验,结果表明给出的方案能大大提高交互式问答文本中指代消解的性能,系统F值提高了3.2%。

Centering Theory and Discourse Structure Based Approach to Coreference Resolution for Interactive Question Answering Text

The interactive question answering texts is rich in linguistic phenomena. Taking this a advantage, a novel coreference resolution approach for interactive question answering text is proposed. On basis of shallow sematic role analysis, the discourse structure is identified, upon which the preferred center and types center shift are further identified. These form a new feature set related to centering theory and discourse structure. Experiments on TREC2004 to TREC2007 corpora show that the proposed approach can significantly improve the performance of coreference resolution about 3.2% in F-measure for interactive question answering texts.