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Open knowledge extraction challenge

Conference Paper
Publication Date:
2015
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.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
knowledge extraction; open inform; challenge
List of contributors:
Nuzzolese, ANDREA GIOVANNI; Gangemi, Aldo; Presutti, Valentina
Authors of the University:
GANGEMI ALDO
NUZZOLESE ANDREA GIOVANNI
Handle:
https://iris.cnr.it/handle/20.500.14243/308162
Published in:
COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE (PRINT)
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http://www.scopus.com/inward/record.url?eid=2-s2.0-84951278244&partnerID=q2rCbXpz
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