Updating a name tagger using contemporary unlabeled data

Cristina Mota, Ralph Grishman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

For many NLP tasks, including named entity tagging, semi-supervised learning has been proposed as a reasonable alternative to methods that require annotating large amounts of training data. In this paper, we address the problem of analyzing new data given a semi-supervised NE tagger trained on data from an earlier time period. We will show that updating the unlabeled data is sufficient to maintain quality over time, and outperforms updating the labeled data. Furthermore, we will also show that augmenting the unlabeled data with older data in most cases does not result in better performance than simply using a smaller amount of current unlabeled data.

Original languageEnglish (US)
Title of host publicationACL-IJCNLP 2009 - Joint Conf. of the 47th Annual Meeting of the Association for Computational Linguistics and 4th Int. Joint Conf. on Natural Language Processing of the AFNLP, Proceedings of the Conf.
PublisherAssociation for Computational Linguistics (ACL)
Pages353-356
Number of pages4
ISBN (Print)9781617382581
DOIs
StatePublished - 2009
EventJoint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and 4th International Joint Conference on Natural Language Processing of the AFNLP, ACL-IJCNLP 2009 - Suntec, Singapore
Duration: Aug 2 2009Aug 7 2009

Publication series

NameACL-IJCNLP 2009 - Joint Conf. of the 47th Annual Meeting of the Association for Computational Linguistics and 4th Int. Joint Conf. on Natural Language Processing of the AFNLP, Proceedings of the Conf.

Other

OtherJoint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and 4th International Joint Conference on Natural Language Processing of the AFNLP, ACL-IJCNLP 2009
CountrySingapore
CitySuntec
Period8/2/098/7/09

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language

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