A hidden Markov model information retrieval system
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Unsupervised learning of soft patterns for generating definitions from online news
Proceedings of the 13th international conference on World Wide Web
Evaluation of an extraction-based approach to answering definitional questions
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Experiments in multi-modal automatic content extraction
HLT '01 Proceedings of the first international conference on Human language technology research
Performance issues and error analysis in an open-domain Question Answering system
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Learning surface text patterns for a Question Answering system
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Automatic evaluation of summaries using N-gram co-occurrence statistics
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
A unified framework for automatic evaluation using N-gram co-occurrence statistics
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Information extraction for question answering: improving recall through syntactic patterns
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Automatically evaluating answers to definition questions
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Soft pattern matching models for definitional question answering
ACM Transactions on Information Systems (TOIS)
Improving web search relevance with semantic features
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
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We explore a hybrid approach for Chinese definitional question answering by combining deep linguistic analysis with surface pattern learning. We answer four questions in this study: 1) How helpful are linguistic analysis and pattern learning? 2) What kind of questions can be answered by pattern matching? 3) How much annotation is required for a pattern-based system to achieve good performance? 4) What linguistic features are most useful? Extensive experiments are conducted on biographical questions and other definitional questions. Major findings include: 1) linguistic analysis and pattern learning are complementary; both are required to make a good definitional QA system; 2) pattern matching is very effective in answering biographical questions while less effective for other definitional questions; 3) only a small amount of annotation is required for a pattern learning system to achieve good performance on biographical questions; 4) the most useful linguistic features are copulas and appositives; relations also play an important role; only some propositions convey vital facts.