The second open knowledge extraction challenge

The Open Knowledge Extraction (OKE) challenge, at its second edition, has the ambition to provide a reference framework for research on Knowledge Extraction from text for the Semantic Web by re-defining a number of tasks (typically from information and knowledge extraction), taking into account specific SW requirements. The OKE challenge defines two tasks: (1) Entity Recognition, Linking and Typing for Knowledge Base population; (2) Class Induction and entity typing for Vocabulary and Knowledge Base enrichment. Task 1 consists of identifying Entities in a sentence and create an OWL individual representing it, link to a reference KB (DBpedia) when possible and assigning a type to such individual. Task 2 consists in producing rdf:type statements, given definition texts. The participants will be given a dataset of sentences, each defining an entity (known a priori). The following systems participated to the challenge: WestLab to both Task 1 and 2, ADEL and Mannheim to Task 2 only. 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. © Springer International Publishing Switzerland 2016.

Publication type: 
Contributo in volume
Author or Creator: 
Nuzzolese Andrea Giovanni
Gentile Anna Lisa.
Presutti Valentina
Gangemi Aldo
Meusel Robert
Paulheim Heiko
Publisher: 
Springer-Verlag, Berlin, DEU
Source: 
The second open knowledge extraction challenge, edited by Dietze S.; Tordai A.; Lange C.; Sack H., pp. 3–16. Berlin: Springer-Verlag, 2016
Date: 
2016
Resource Identifier: 
http://www.cnr.it/prodotto/i/366561
https://dx.doi.org/10.1007/978-3-319-46565-4_1
info:doi:10.1007/978-3-319-46565-4_1
http://www.scopus.com/record/display.url?eid=2-s2.0-84992445789&origin=inward
Language: 
Eng
ISTC Author: 
Aldo Gangemi's picture
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Valentina Presutti's picture
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Andrea Nuzzolese's picture
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