[3G1-ES-1] Knowledge engineering (1)

[3G1-ES-1-01] Identification of Correct Triples on Open Information Extraction

〇Esrat Farjana¹, Natthawut KertKeidkachorn², Ryutaro Ichise^1,2,3 (1. The Graduate University for Advanced Studies, SOKENDAI, 2. National Institute of Advanced Industrial Science and Technology, 3. National Institute of Informatics)

Keywords:Knowledge Graph, Noisy Triple, Open Information Extraction

Knowledge Graph (KG) is a key component of many information systems. Due to the drastic growth of the text data, Open Information Extraction (Open IE) becomes one of the techniques to build Knowledge Graph. Nevertheless, OpenIE usually generates many noisy triples. Populating a knowledge graph with such triples degrades its quality. In this study, we introduced novel features to identify correct triples, extracted by the OpenIE system. Experimental results showed that our features achieved better results compared to the baseline features.