Semantic Web Evaluation Challenge

Semantic Web Evaluation Challenges pp 3-15

Open Knowledge Extraction Challenge

  • Andrea Giovanni Nuzzolese
  • Anna Lisa Gentile
  • Valentina Presutti
  • Aldo Gangemi
  • Darío Garigliotti
  • Roberto Navigli
Conference paper

DOI: 10.1007/978-3-319-25518-7_1

Part of the Communications in Computer and Information Science book series (CCIS, volume 548)
Cite this paper as:
Nuzzolese A.G., Gentile A.L., Presutti V., Gangemi A., Garigliotti D., Navigli R. (2015) Open Knowledge Extraction Challenge. In: Gandon F., Cabrio E., Stankovic M., Zimmermann A. (eds) Semantic Web Evaluation Challenges. Communications in Computer and Information Science, vol 548. Springer, Cham

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.

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Andrea Giovanni Nuzzolese
    • 1
  • Anna Lisa Gentile
    • 2
  • Valentina Presutti
    • 1
  • Aldo Gangemi
    • 1
  • Darío Garigliotti
    • 3
  • Roberto Navigli
    • 3
  1. 1.Semantic Technology Lab, ISTC-CNRRomeItaly
  2. 2.Department of Computer ScienceUniversity of SheffieldSheffieldUK
  3. 3.Department of Computer ScienceSapienza University of RomeRomeItaly

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