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KUL: Recognition and normalization of temporal expressions

Authors:

Oleksandr Kolomiyets,

Marie-Francine MoensAuthors Info & Claims

SemEval '10: Proceedings of the 5th International Workshop on Semantic Evaluation

Pages 325 - 328

Published: 15 July 2010 Publication History

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Abstract

In this paper we describe a system for the recognition and normalization of temporal expressions (Task 13: TempEval-2, Task A). The recognition task is approached as a classification problem of sentence constituents and the normalization is implemented in a rule-based manner. One of the system features is extending positive annotations in the corpus by semantically similar words automatically obtained from a large unannotated textual corpus. The best results obtained by the system are 0.85 and 0.84 for precision and recall respectively for recognition of temporal expressions; the accuracy values of 0.91 and 0.55 were obtained for the feature values type and val respectively.

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Llorens HSaquete ENavarro-Colorado B(2013)Applying semantic knowledge to the automatic processing of temporal expressions and events in natural languageInformation Processing and Management: an International Journal10.1016/j.ipm.2012.05.00549:1(179-197)Online publication date: 1-Jan-2013
https://dl.acm.org/doi/10.1016/j.ipm.2012.05.005
Angeli GManning CJurafsky DChu-Carroll J(2012)Parsing timeProceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies10.5555/2382029.2382092(446-455)Online publication date: 3-Jun-2012
https://dl.acm.org/doi/10.5555/2382029.2382092
Llorens HSaquete ENavarro B(2011)Syntax-motivated context windows of morpho-lexical features for recognizing time and event expressions in natural languageProceedings of the 16th international conference on Natural language processing and information systems10.5555/2026011.2026056(295-299)Online publication date: 28-Jun-2011
https://dl.acm.org/doi/10.5555/2026011.2026056
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Index Terms

KUL: Recognition and normalization of temporal expressions
1. Applied computing
  1. Document management and text processing
2. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing

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Published In

SemEval '10: Proceedings of the 5th International Workshop on Semantic Evaluation

July 2010

473 pages

Program Chairs:
Katrin Erk
University of Texas at Austin
,
Carlo Strapparava
ITC IRST

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Association for Computational Linguistics

United States

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Published: 15 July 2010

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Overall Acceptance Rate 8 of 31 submissions, 26%

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Llorens HSaquete ENavarro-Colorado B(2013)Applying semantic knowledge to the automatic processing of temporal expressions and events in natural languageInformation Processing and Management: an International Journal10.1016/j.ipm.2012.05.00549:1(179-197)Online publication date: 1-Jan-2013
https://dl.acm.org/doi/10.1016/j.ipm.2012.05.005
Angeli GManning CJurafsky DChu-Carroll J(2012)Parsing timeProceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies10.5555/2382029.2382092(446-455)Online publication date: 3-Jun-2012
https://dl.acm.org/doi/10.5555/2382029.2382092
Llorens HSaquete ENavarro B(2011)Syntax-motivated context windows of morpho-lexical features for recognizing time and event expressions in natural languageProceedings of the 16th international conference on Natural language processing and information systems10.5555/2026011.2026056(295-299)Online publication date: 28-Jun-2011
https://dl.acm.org/doi/10.5555/2026011.2026056
Kolomiyets OBethard SMoens MLin D(2011)Model-portability experiments for textual temporal analysisProceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 210.5555/2002736.2002793(271-276)Online publication date: 19-Jun-2011
https://dl.acm.org/doi/10.5555/2002736.2002793

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Abstract

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Cited By

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Recommendations

Combining automatic acquisition of knowledge with machine learning approaches for multilingual temporal recognition and normalization

Face Recognition Through Different Facial Expressions

Portuguese Temporal Expressions Recognition: From TE Characterization to an Effective TER Module Implementation

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