TY - GEN
T1 - Framester
T2 - 20th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2016 Satellite Events, EKM and Drift-an-LOD, Revised Selected Paper
AU - Gangemi, Aldo
AU - Alam, Mehwish
AU - Asprino, Luigi
AU - Presutti, Valentina
AU - Recupero, Diego Reforgiato
N1 - Publisher Copyright:
© Springer International Publishing AG 2016.
PY - 2016/1/1
Y1 - 2016/1/1
N2 - Semantic web applications leveraging NLP can benefit from easy access to expressive lexical resources such as FrameNet. However, the usefulness of FrameNet is affected by its limited coverage and nonstandard semantics. The access to existing linguistic resources is also limited because of poor connectivity among them. We present some strategies based on Linguistic Linked Data to broaden FrameNet coverage and formal linkage of lexical and factual resources. We created a novel resource, Framester, which acts as a hub between FrameNet, Word- Net, VerbNet, BabelNet, DBpedia, Yago, DOLCE-Zero, as well as other resources. Framester is not only a strongly connected knowledge graph, but also applies a rigorous formal treatment for Fillmore’s frame semantics, enabling full-fledged OWL querying and reasoning on a large framebased knowledge graph. We also describe Word Frame Disambiguation, an application that reuses Framester data as a base in order to perform frame detection from text, with results comparable in precision to the state of the art, but with a much higher coverage.
AB - Semantic web applications leveraging NLP can benefit from easy access to expressive lexical resources such as FrameNet. However, the usefulness of FrameNet is affected by its limited coverage and nonstandard semantics. The access to existing linguistic resources is also limited because of poor connectivity among them. We present some strategies based on Linguistic Linked Data to broaden FrameNet coverage and formal linkage of lexical and factual resources. We created a novel resource, Framester, which acts as a hub between FrameNet, Word- Net, VerbNet, BabelNet, DBpedia, Yago, DOLCE-Zero, as well as other resources. Framester is not only a strongly connected knowledge graph, but also applies a rigorous formal treatment for Fillmore’s frame semantics, enabling full-fledged OWL querying and reasoning on a large framebased knowledge graph. We also describe Word Frame Disambiguation, an application that reuses Framester data as a base in order to perform frame detection from text, with results comparable in precision to the state of the art, but with a much higher coverage.
KW - Frame detection
KW - Frame semantics
KW - FrameNet
KW - Framenet coverage
KW - Framester
KW - Knowledge graphs
KW - Linguistic linked data
UR - https://www.scopus.com/pages/publications/84997124448
U2 - 10.1007/978-3-319-49004-5_16
DO - 10.1007/978-3-319-49004-5_16
M3 - Conference contribution
AN - SCOPUS:84997124448
SN - 9783319490038
T3 - Lecture Notes in Computer Science
SP - 239
EP - 254
BT - Knowledge Engineering and Knowledge Management - 20th International Conference, EKAW 2016, Proceedings
A2 - Blomqvist, Eva
A2 - Ciancarini, Paolo
A2 - Poggi, Francesco
A2 - Vitali, Fabio
PB - Springer Verlag
Y2 - 19 November 2016 through 23 November 2016
ER -