In this demonstration we showcase PIKES, a Semantic Role Labeling (SRL)-powered approach for Knowledge Extraction. PIKES implements a rule-based strategy that reinterprets SRL output in light of other linguistic analyses, such as dependency parsing and co-reference resolution, thus properly capturing and formalizing in RDF important linguistic aspects such as argument nominalization, frame-frame relations, and group entities.
In this demonstration we showcase PIKES, a Semantic Role Labeling (SRL)-powered approach for Knowledge Extraction. PIKES implements a rule-based strategy that reinterprets SRL output in light of other linguistic analyses, such as dependency parsing and co-reference resolution, thus properly capturing and formalizing in RDF important linguistic aspects such as argument nominalization, frame-frame relations, and group entities.
Extracting Knowledge from Text with PIKES / Corcoglioniti, Francesco; Rospocher, Marco; Palmero Aprosio, Alessio. - ELETTRONICO. - 1486:(2015). ( ISWC 2015 Posters and Demonstrations Track, ISWC-P and D 2015 - co-located with the 14th International Semantic Web Conference, ISWC 2015 Bethlehem, Pennsylvania October 11-15, 2015).
Extracting Knowledge from Text with PIKES
Corcoglioniti, Francesco;Rospocher, Marco;Palmero Aprosio, Alessio
2015-01-01
Abstract
In this demonstration we showcase PIKES, a Semantic Role Labeling (SRL)-powered approach for Knowledge Extraction. PIKES implements a rule-based strategy that reinterprets SRL output in light of other linguistic analyses, such as dependency parsing and co-reference resolution, thus properly capturing and formalizing in RDF important linguistic aspects such as argument nominalization, frame-frame relations, and group entities.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione
