Sentence boundary detection and the problem with the U.S.

NAACL-HLT 2009 - Human Language Technologies: 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Short Papers

Volumn , Issue , 2009, Pages 241-244

  Gillick, Dan ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ERROR RATE; NEWS CORPORA; SENTENCE BOUNDARY DETECTION; STATISTICAL SYSTEMS;

COMPUTATIONAL LINGUISTICS;

EID: 84875417937     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

1. J. Aberdeen, J. Burger, D. Day, L. Hirschman, P. Robinson, and M. Vilain. 1995. MITRE: description of the Alembic system used for MUC-6. In Proceedings of the 6th conference on Message understanding, pages 141–155. Association for Computational Linguistics Morristown, NJ, USA.
2. T. Joachims. 1999. Making large-scale support vector machine learning practical, Advances in kernel methods: support vector learning.
3. T. Kiss and J. Strunk. 2006. Unsupervised Multilingual Sentence Boundary Detection. Computational Linguistics, 32(4):485–525.
4. E. Loper and S. Bird. 2002. NLTK: The Natural Language Toolkit. In Proceedings of the ACL Workshop on Effective Tools and Methodologies for Teaching Natural Language Processing and Computational Linguistics, pages 62–69.
5. M.P. Marcus, M.A. Marcinkiewicz, and B. Santorini. 1993. Building a large annotated corpus of English: the penn treebank. Computational Linguistics, 19(2):313–330.
6. A. Mikheev. 2002. Periods, Capitalized Words, etc. Computational Linguistics, 28(3):289–318.
7. D.D. Palmer and M.A. Hearst. 1997. Adaptive Multilingual Sentence Boundary Disambiguation. Computational Linguistics, 23(2):241–267.
8. J.C. Reynar and A. Ratnaparkhi. 1997. A maximum entropy approach to identifying sentence boundaries. In Proceedings of the Fifth Conference on Applied Natural Language Processing, pages 16–19.