Summary of the paper
| Title | Using Dialogue Corpora to Extend Information Extraction Patterns for Natural Language Understanding of Dialogue |
|---|---|
| Authors | Roberta Catizone, Alexiei Dingli and Robert Gaizauskas |
| Abstract | This paper examines how Natural Language Process (NLP) resources and online dialogue corpora can be used to extend coverage of Information Extraction (IE) templates in a Spoken Dialogue system. IE templates are used as part of a Natural Language Understanding module for identifying meaning in a user utterance. The use of NLP tools in Dialogue systems is a difficult task given 1) spoken dialogue is often not well-formed and 2) there is a serious lack of dialogue data. In spite of that, we have devised a method for extending IE patterns using standard NLP tools and available dialogue corpora found on the web. In this paper, we explain our method which includes using a set of NLP modules developed using GATE (a General Architecture for Text Engineering), as well as a general purpose editing tool that we built to facilitate the IE rule creation process. Lastly, we present directions for future work in this area. |
| Topics | Information Extraction, Information Retrieval, Dialogue, Named Entity recognition |
Full paper |
Using Dialogue Corpora to Extend Information Extraction Patterns for Natural Language Understanding of Dialogue |
Slides |
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| Bibtex | @InProceedings{CATIZONE10.818, author = {Roberta Catizone and Alexiei Dingli and Robert Gaizauskas}, title = {Using Dialogue Corpora to Extend Information Extraction Patterns for Natural Language Understanding of Dialogue}, booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)}, year = {2010}, month = {may}, date = {19-21}, address = {Valletta, Malta}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-6-7}, language = {english} } |