Automatic labeling of semantic roles
Computational Linguistics
Target word detection and semantic role chunking using support vector machines
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
The Proposition Bank: An Annotated Corpus of Semantic Roles
Computational Linguistics
A semantic approach to boost passage retrieval effectiveness for question answering
ACSC '06 Proceedings of the 29th Australasian Computer Science Conference - Volume 48
Question answering based on semantic structures
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Corpus-based semantic role approach in information retrieval
Data & Knowledge Engineering
Question answering based on semantic roles
DeepLP '07 Proceedings of the Workshop on Deep Linguistic Processing
The role of verb sense disambiguation in semantic role labeling
FinTAL'06 Proceedings of the 5th international conference on Advances in Natural Language Processing
Using semantic constraints to improve question answering
NLDB'06 Proceedings of the 11th international conference on Applications of Natural Language to Information Systems
A hybrid question answering schema using encapsulated semantics in lexical resources
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
From Semantic Roles to Temporal Information Representation
MICAI '09 Proceedings of the 8th Mexican International Conference on Artificial Intelligence
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The contribution of semantic roles to question answering is considered to be very valuable. Due to this fact, the aim of this paper is to analyze the influence of semantic roles in this area. In order to achieve this goal a web QA system has been implemented using two different proposals for the answer extraction module based on semantic roles, and both implementations have been evaluated for location type questions. For the first proposal, a simple set of semantic rules was created, whereas, for the second proposal, a database of possible answer semantic patterns was automatically developed. This DB is created in a first step and it will be reused each time the answer extraction module is used. Results of both approaches have been analyzed and compared showing that the patterns-based approach improves the rules-based one in precision (+ 34.40%) and recall (+ 42.80%).