@inproceedings{berglund-etal-2006-extraction,
title = "Extraction of Temporal Information from Texts in {S}wedish",
author = "Berglund, Anders and
Johansson, Richard and
Nugues, Pierre",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Gangemi, Aldo and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Tapias, Daniel",
booktitle = "Proceedings of the Fifth International Conference on Language Resources and Evaluation ({LREC}{'}06)",
month = may,
year = "2006",
address = "Genoa, Italy",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2006/pdf/10_pdf.pdf",
abstract = "This paper describes the implementation and evaluation of a generic component to extract temporal information from texts in Swedish. It proceeds in two steps. The first step extracts time expressions and events, and generates a feature vector for each element it identifies. Using the vectors, the second step determines the temporal relations, possibly none, between the extracted events and orders them in time. We used a machine learning approach to find the relations between events. To run the learning algorithm, we collected a corpus of road accident reports from newspapers websites that we manually annotated. It enabled us to train decision trees and to evaluate the performance of the algorithm.",
}
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<abstract>This paper describes the implementation and evaluation of a generic component to extract temporal information from texts in Swedish. It proceeds in two steps. The first step extracts time expressions and events, and generates a feature vector for each element it identifies. Using the vectors, the second step determines the temporal relations, possibly none, between the extracted events and orders them in time. We used a machine learning approach to find the relations between events. To run the learning algorithm, we collected a corpus of road accident reports from newspapers websites that we manually annotated. It enabled us to train decision trees and to evaluate the performance of the algorithm.</abstract>
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%0 Conference Proceedings
%T Extraction of Temporal Information from Texts in Swedish
%A Berglund, Anders
%A Johansson, Richard
%A Nugues, Pierre
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Gangemi, Aldo
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Tapias, Daniel
%S Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
%D 2006
%8 May
%I European Language Resources Association (ELRA)
%C Genoa, Italy
%F berglund-etal-2006-extraction
%X This paper describes the implementation and evaluation of a generic component to extract temporal information from texts in Swedish. It proceeds in two steps. The first step extracts time expressions and events, and generates a feature vector for each element it identifies. Using the vectors, the second step determines the temporal relations, possibly none, between the extracted events and orders them in time. We used a machine learning approach to find the relations between events. To run the learning algorithm, we collected a corpus of road accident reports from newspapers websites that we manually annotated. It enabled us to train decision trees and to evaluate the performance of the algorithm.
%U http://www.lrec-conf.org/proceedings/lrec2006/pdf/10_pdf.pdf
Markdown (Informal)
[Extraction of Temporal Information from Texts in Swedish](http://www.lrec-conf.org/proceedings/lrec2006/pdf/10_pdf.pdf) (Berglund et al., LREC 2006)
ACL
- Anders Berglund, Richard Johansson, and Pierre Nugues. 2006. Extraction of Temporal Information from Texts in Swedish. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06), Genoa, Italy. European Language Resources Association (ELRA).