Extracting knowledge from text using SHELDON, a semantic holistic framEwork for LinkeD ONtology data

SHELDON1 is the first true hybridization of NLP machine reading and the Semantic Web. It extracts RDF data from text using a machine reader: the extracted RDF graphs are compliant to Semantic Web and Linked Data. It goes further and applies Semantic Web practices and technolo- gies to extend the current human-readable web. The input is represented by a sentence in any language. SHELDON includes different capabilities in order to extend machine reading to Semantic Web data: frame detection, topic ex- traction, named entity recognition, resolution and corefer- ence, terminology extraction, sense tagging and disambigua- tion, taxonomy induction, semantic role labeling, type in- duction, sentiment analysis, citation inference, relation and event extraction, nice visualization tools which make use of the JavaScript infoVis Toolkit and RelFinder. A demo of SHELDON can be seen and used at http://wit.istc.cnr. it/stlab-tools/sheldon.

Tipo Pubblicazione: 
Contributo in atti di convegno
Author or Creator: 
Recupero, Diego Reforgiato
Nuzzolese, Andrea Giovanni
Consoli, Sergio
Presutti, Valentina
Peroni, Silvio
Mongiovì, Misael
24th International Conference on World Wide Web (WWW2015), pp. 235–238, Florence, Italy, 18-22/05/2015
info:cnr-pdr/source/autori:Recupero, Diego Reforgiato; Nuzzolese, Andrea Giovanni; Consoli, Sergio; Presutti, Valentina; Peroni, Silvio; Mongiovì, Misael/congresso_nome:24th International Conference on World Wide Web (WWW2015)/congresso_luogo:Florence, It
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