Paper Info
Title
Data-Driven and Ontological Analysis of FrameNet for Natural Language Reasoning
Abstract
This paper focuses on the improvement of the conceptual structure of FrameNet for the sake of applying this resource to knowledge- intensive NLP tasks requiring reasoning, such as question answering, information extraction etc. Ontological analysis supported by data-driven methods is used for axiomatizing, enriching and cleaning up frame relations. The impact of the achieved axiomatization is investigated on recognizing textual entailment.
Year
Venue
Keywords
2010
LREC 2010 - SEVENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
natural language,question answering,information extraction
Field
DocType
Citations 
Ontology,Question answering,Data-driven,Textual entailment,Information retrieval,Computer science,Information extraction,Natural language,Language identification,Artificial intelligence,Natural language processing,FrameNet
Conference
10
PageRank 
References 
Authors
0.74
10
5
Name
Order
Citations
PageRank
Ekaterina Ovchinnikova1586.56
Laure Vieu238737.29
Alessandro Oltramari373587.68
STEFANO BORGO428944.72
Theodore Alexandrov5292.99