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Authors: Cleiton Fernando Lima Sena ; Rafael Glauber and Daniela Barreiro Claro

Affiliation: Federal University of Bahia (UFBA), Brazil

ISBN: 978-989-758-247-9

Keyword(s): Open Information Extraction, Inference, Transitivity, Symmetry, Portuguese.

Related Ontology Subjects/Areas/Topics: Applications of Expert Systems ; Artificial Intelligence and Decision Support Systems ; Enterprise Information Systems ; Natural Language Interfaces to Intelligent Systems

Abstract: Open Information Extraction (Open IE) enables the extraction of facts in large quantities of texts written in natural language. Despite the fact that almost research has been doing in English texts, methods and techniques for other languages have been less frequent. However, those languages other than English correspond to 48% of content available on websites around the world. In this work, we propose a method for extracting facts in Portuguese without pre-determining the types of the facts. Additionally, we increased the quantity of those extracted facts by the use of an inference approach. Our inference method is composed of two issues: a transitive and a symmetric mechanism. To the best of our knowledge, this is the first time that inference approach is used to extract facts in Portuguese texts. Our proposal allowed an increase of 36% in quantity of valid facts extracted in a Portuguese Open IE system, and it is compatible in the quality of facts with English approaches.

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Paper citation in several formats:
Lima Sena, C.; Glauber, R. and Claro, D. B. (2017). Inference Approach to Enhance a Portuguese Open Information Extraction.In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-247-9, pages 442-451. DOI: 10.5220/0006338204420451

@conference{iceis17,
author={Cleiton Fernando Lima Sena. and Rafael Glauber. and Claro, D. B.},
title={Inference Approach to Enhance a Portuguese Open Information Extraction},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2017},
pages={442-451},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006338204420451},
isbn={978-989-758-247-9},
}

TY - CONF

JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Inference Approach to Enhance a Portuguese Open Information Extraction
SN - 978-989-758-247-9
AU - Lima Sena, C.
AU - Glauber, R.
AU - Claro, D. B.
PY - 2017
SP - 442
EP - 451
DO - 10.5220/0006338204420451

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