Open Knowledge Extraction Challenge
Communications in computer and information sciencePublished 1 January 2015
Andrea Giovanni Nuzzolese, Anna Lisa Gentile, Valentina Presutti, Aldo Gangemi, Darío Garigliotti, Roberto Navigli
Citations45
SJR quartileQ4
SJR score0.18
SNIP0.24
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TL;DR
The OKE challenge, the tasks, the datasets used for training and evaluating the systems, the evaluation method, and obtained results are described.
Abstract
The Open Knowledge Extraction (OKE) challenge is aimed at promoting research in the automatic extraction of structured content from textual data and its representation and publication as Linked Data. We designed two extraction tasks: (1) Entity Recognition, Linking and Typing and (2) Class Induction and entity typing. The challenge saw the participations of four systems: CETUS-FOX and FRED participating to both tasks, Adel participating to Task 1 and OAK@Sheffield participating to Task 2. In this paper we describe the OKE challenge, the tasks, the datasets used for training and evaluating the systems, the evaluation method, and obtained results.
Keywords
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