Abstract
This paper shows the precision, the recall and the F-measure for the knowledge extraction methods (under Open Information Extraction paradigm): ReVerb, OLLIE and ClausIE. For obtaining these three measures a subset of 55 newswires corpus was used. This subset was taken from the Reuters-21578 text categorization and test collection database. A handmade relation extraction was applied for each one of these newswires.
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Acknowledgments
The research reported in this paper was partially funded by Projects UNLa-33A205 and UNLa-33B177 of National University of Lanus (Argentina). Authors wish to thank to senior students in our courses within Information Engineering Bachelor Degree at Engineering School - University of Buenos Aires for their help during the experiment.
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Rodríguez, J.M., Merlino, H.D., Pesado, P., García-Martínez, R. (2016). Performance Evaluation of Knowledge Extraction Methods. In: Fujita, H., Ali, M., Selamat, A., Sasaki, J., Kurematsu, M. (eds) Trends in Applied Knowledge-Based Systems and Data Science. IEA/AIE 2016. Lecture Notes in Computer Science(), vol 9799. Springer, Cham. https://doi.org/10.1007/978-3-319-42007-3_2
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