Paper Info
Title
A novel Framenet-based resource for the semantic web
Abstract
FrameNet is a large-scale lexical resource encoding information about semantic frames (situations) and semantic roles. The aim of the paper is to enrich FrameNet by mapping the lexical fillers of semantic roles to WordNet using a Wikipedia-based detour. The applied methodology relies on a word sense disambiguation step, in which a Wikipedia page is assigned to a role filler, and then BabelNet and YAGO are used to acquire WordNet synsets for a filler. We show how to represent the acquired resource in OWL, linking it to the existing RDF/OWL representations of FrameNet and WordNet. Part of the resource is evaluated by matching it with the WordNet synsets manually assigned by FrameNet lexicographers to a subset of semantic roles.
Year
DOI
Venue
2012
10.1145/2245276.2245346
SAC
Keywords
Field
DocType
role filler,large-scale lexical resource,novel framenet-based resource,wikipedia page,semantic frame,acquired resource,wordnet synsets,owl representation,lexical filler,semantic role,semantic web,framenet lexicographer,owl,framenet,wordnet
Information retrieval,Computer science,Semantic Web,Natural language processing,Artificial intelligence,WordNet,Lexicography,RDF,Word-sense disambiguation,Semantic role labeling,FrameNet,Encoding (memory)
Conference
Citations 
PageRank 
References 
7
0.57
15
Authors
4
Name
Order
Citations
PageRank
Volha Bryl118014.46
Sara Tonelli2824.66
Claudio Giuliano348833.00
Luciano Serafini42230204.36