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Extraction of temporal information from texts in Swedish

Berglund, Anders; Johansson, Richard LU and Nugues, Pierre LU (2006) LREC-2006, The fifth international conference on Language Resources and Evaluation In Proceedings of LREC-2006, The fifth international conference on Language Resources and Evaluation p.259-264
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.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
information extraction, semantic analysis, temporal relations, Natural language processing
in
Proceedings of LREC-2006, The fifth international conference on Language Resources and Evaluation
pages
6 pages
conference name
LREC-2006, The fifth international conference on Language Resources and Evaluation
language
English
LU publication?
yes
id
420cbd96-d0df-488d-b59d-cb7c17d240ab (old id 630377)
alternative location
http://www.cs.lth.se/~pierre/Articles/lrec2006/lrec2006_time.pdf
date added to LUP
2007-11-28 10:58:15
date last changed
2016-04-16 12:46:24
@inproceedings{420cbd96-d0df-488d-b59d-cb7c17d240ab,
  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<br/><br>
temporal relations, possibly none, between the extracted events and orders them in time.<br/><br>
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.},
  author       = {Berglund, Anders and Johansson, Richard and Nugues, Pierre},
  booktitle    = {Proceedings of LREC-2006, The fifth international conference on Language Resources and Evaluation},
  keyword      = {information extraction,semantic analysis,temporal relations,Natural language processing},
  language     = {eng},
  pages        = {259--264},
  title        = {Extraction of temporal information from texts in Swedish},
  year         = {2006},
}