The nature of statistical learning theory
The nature of statistical learning theory
Question-answering by predictive annotation
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Bridging the lexical chasm: statistical approaches to answer-finding
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Learning search engine specific query transformations for question answering
Proceedings of the 10th international conference on World Wide Web
GETESS - Searching the Web Exploiting German Texts
CIA '99 Proceedings of the Third International Workshop on Cooperative Information Agents III
Analysis of Statistical Question Classification for Fact-Based Questions
Information Retrieval
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Automatic derivation of surface text patterns for a maximum entropy based question answering system
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
AquaLog: An ontology-driven question answering system for organizational semantic intranets
Web Semantics: Science, Services and Agents on the World Wide Web
Question answering system based on ontology and semantic web
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
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This paper presents our research related to automatic Expected Answer Type and Named Entity annotation tasks in a Question Answering context. We present the initial step of our research, in which we created the annotation guidelines. We therefore show and justify the tag set employed in the annotation of a collection of questions, and finally, different evaluations in order to test the consistency of the labelled corpus are also presented.