@inproceedings{llorens-etal-2012-timen,
title = "{TIMEN}: An Open Temporal Expression Normalisation Resource",
author = "Llorens, Hector and
Derczynski, Leon and
Gaizauskas, Robert and
Saquete, Estela",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Do{\u{g}}an, Mehmet U{\u{g}}ur and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Eighth International Conference on Language Resources and Evaluation ({LREC}'12)",
month = may,
year = "2012",
address = "Istanbul, Turkey",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2012/pdf/128_Paper.pdf",
pages = "3044--3051",
abstract = "Temporal expressions are words or phrases that describe a point, duration or recurrence in time. Automatically annotating these expressions is a research goal of increasing interest. Recognising them can be achieved with minimally supervised machine learning, but interpreting them accurately (normalisation) is a complex task requiring human knowledge. In this paper, we present TIMEN, a community-driven tool for temporal expression normalisation. TIMEN is derived from current best approaches and is an independent tool, enabling easy integration in existing systems. We argue that temporal expression normalisation can only be effectively performed with a large knowledge base and set of rules. Our solution is a framework and system with which to capture this knowledge for different languages. Using both existing and newly-annotated data, we present results showing competitive performance and invite the IE community to contribute to a knowledge base in order to solve the temporal expression normalisation problem.",
}
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<abstract>Temporal expressions are words or phrases that describe a point, duration or recurrence in time. Automatically annotating these expressions is a research goal of increasing interest. Recognising them can be achieved with minimally supervised machine learning, but interpreting them accurately (normalisation) is a complex task requiring human knowledge. In this paper, we present TIMEN, a community-driven tool for temporal expression normalisation. TIMEN is derived from current best approaches and is an independent tool, enabling easy integration in existing systems. We argue that temporal expression normalisation can only be effectively performed with a large knowledge base and set of rules. Our solution is a framework and system with which to capture this knowledge for different languages. Using both existing and newly-annotated data, we present results showing competitive performance and invite the IE community to contribute to a knowledge base in order to solve the temporal expression normalisation problem.</abstract>
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%0 Conference Proceedings
%T TIMEN: An Open Temporal Expression Normalisation Resource
%A Llorens, Hector
%A Derczynski, Leon
%A Gaizauskas, Robert
%A Saquete, Estela
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Doğan, Mehmet Uğur
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC’12)
%D 2012
%8 May
%I European Language Resources Association (ELRA)
%C Istanbul, Turkey
%F llorens-etal-2012-timen
%X Temporal expressions are words or phrases that describe a point, duration or recurrence in time. Automatically annotating these expressions is a research goal of increasing interest. Recognising them can be achieved with minimally supervised machine learning, but interpreting them accurately (normalisation) is a complex task requiring human knowledge. In this paper, we present TIMEN, a community-driven tool for temporal expression normalisation. TIMEN is derived from current best approaches and is an independent tool, enabling easy integration in existing systems. We argue that temporal expression normalisation can only be effectively performed with a large knowledge base and set of rules. Our solution is a framework and system with which to capture this knowledge for different languages. Using both existing and newly-annotated data, we present results showing competitive performance and invite the IE community to contribute to a knowledge base in order to solve the temporal expression normalisation problem.
%U http://www.lrec-conf.org/proceedings/lrec2012/pdf/128_Paper.pdf
%P 3044-3051
Markdown (Informal)
[TIMEN: An Open Temporal Expression Normalisation Resource](http://www.lrec-conf.org/proceedings/lrec2012/pdf/128_Paper.pdf) (Llorens et al., LREC 2012)
ACL
- Hector Llorens, Leon Derczynski, Robert Gaizauskas, and Estela Saquete. 2012. TIMEN: An Open Temporal Expression Normalisation Resource. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), pages 3044–3051, Istanbul, Turkey. European Language Resources Association (ELRA).