Evaluation of open information extraction methods using Reuters-21578 database

Título:

Evaluation of open information extraction methods using Reuters-21578 database

Autor:

Rodríguez, J. M.

Colaboradores:

; Merlino, Hernán; Pesado, Patricia Mabel; García-Martínez, Ramón

Temas:

En:

International Conference on Machine Learning and Soft Computing (2da : 2018 : Phu Quoc, Vietnam)

Resumen:

The following article shows the precision, the recall and the F1-measure for three knowledge extraction methods under Open Information Extraction paradigm. These methods are: ReVerb, OLLIE and ClausIE. For the calculation of these three measures, a representative sample of Reuters-21578 was used; 103 newswire texts were taken randomly from that database. A big discrepancy was observed, after analyzing the obtained results, between the expected and the observed precision for ClausIE. In order to save the observed gap in ClausIE precision, a simple improvement is proposed for the method. Although the correction improved the precision of Clausie, ReVerb turned out to be the most precise method; however ClausIE is the one with the better F1-measure.

URL/DOI:

http://dx.doi.org/10.1145/3184066.3184099

Medio:

Soporte electrónico

Tipo de documento:

Artículo

Descripción física:

1 archivo (375,3 kB)

Idioma:

Inglés

Publicación:

, 2018

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