Automatic Identification of Non-Anaphoric Anaphora in Spoken Dialog

摘要：

Identification of non-anaphoric anaphora is an important step towards a full anaphora resolution. In this paper, we present an automatic identification approach for this task. In our work, some novel features are proposed, which are based on dependency grammars, surrounding words and their POS tags. All the features are automatically extracted using a part-of-speech (POS) tagger and a dependency parser. Our experiments are on a commonly available dialogue corpus, Trains-93. Several machine learning algorithms are used in the experiments, including CME, CRF and SVM. Results show that compared to the approaches used in the previous work, our algorithm is simpler and achieves a higher accuracy.

关键词： Spoken dialog anaphora resolution non-anaphoric anaphora identification

作者: Zhongchao FEI Xuanjing HUANG Fuliang WENG

作者单位: Department of Computer Science,Fudan University Shanghai,China Research and Technology Center,Robert Bosch LLC Palo Alto,CA,United States

会议类型: 国际会议

会议名称: The 2008 IEEE International Conference on Natural Language Processing and Knowledge Engineering(IEEE NLP-KE 2008)(2008IEEE自然语言处理与知识工程国际会议)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-19（万方平台首次上网日期，不代表论文的发表时间）