A Sequence Model Approach to Relation Extraction in Portuguese

Sandra Collovini, Gabriel Machado, Renata Vieira


Abstract
The task of Relation Extraction from texts is one of the main challenges in the area of Information Extraction, considering the required linguistic knowledge and the sophistication of the language processing techniques employed. This task aims at identifying and classifying semantic relations that occur between entities recognized in a given text. In this paper, we evaluated a Conditional Random Fields classifier for the extraction of any relation descriptor occurring between named entities (Organisation, Person and Place categories), as well as pre-defined relation types between these entities in Portuguese texts.
Anthology ID:
L16-1301
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
1908–1912
Language:
URL:
https://aclanthology.org/L16-1301
DOI:
Bibkey:
Cite (ACL):
Sandra Collovini, Gabriel Machado, and Renata Vieira. 2016. A Sequence Model Approach to Relation Extraction in Portuguese. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 1908–1912, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
A Sequence Model Approach to Relation Extraction in Portuguese (Collovini et al., LREC 2016)
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PDF:
https://aclanthology.org/L16-1301.pdf