Automatic semantic relation extraction from Portuguese texts

Leonardo Sameshima Taba, Helena Caseli

Abstract
Nowadays we are facing a growing demand for semantic knowledge in computational applications, particularly in Natural Language Processing (NLP). However, there aren’t sufficient human resources to produce that knowledge at the same rate of its demand. Considering the Portuguese language, which has few resources in the semantic area, the situation is even more alarming. Aiming to solve that problem, this work investigates how some semantic relations can be automatically extracted from Portuguese texts. The two main approaches investigated here are based on (i) textual patterns and (ii) machine learning algorithms. Thus, this work investigates how and to which extent these two approaches can be applied to the automatic extraction of seven binary semantic relations (is-a, part-of, location-of, effect-of, property-of, made-of and used-for) in Portuguese texts. The results indicate that machine learning, in particular Support Vector Machines, is a promising technique for the task, although textual patterns presented better results for the used-for relation.
Anthology ID:
L14-1434
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
2739–2746
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/522_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Leonardo Sameshima Taba and Helena Caseli. 2014. Automatic semantic relation extraction from Portuguese texts. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 2739–2746, Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
Automatic semantic relation extraction from Portuguese texts (Taba & Caseli, LREC 2014)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/522_Paper.pdf
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