Building a question answering test collection
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Class-Based Construction of a Verb Lexicon
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Toward semantics-based answer pinpointing
HLT '01 Proceedings of the first international conference on Human language technology research
The structure and performance of an open-domain question answering system
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Retrieving answers from frequently asked questions pages on the web
Proceedings of the 14th ACM international conference on Information and knowledge management
A question/answer typology with surface text patterns
HLT '02 Proceedings of the second international conference on Human Language Technology Research
ACM Transactions on Asian Language Information Processing (TALIP)
Why text segment classification based on part of speech feature selection
DS'10 Proceedings of the 13th international conference on Discovery science
What is not in the bag of words for why-qa?
Computational Linguistics
Medical question answering: translating medical questions into sparql queries
Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
Compact explanatory opinion summarization
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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In the current project, we aim at developing an approach for automatically answering why-questions. We created a data collection for research, development and evaluation of a method for automatically answering why-questions (why-QA) The resulting collection comprises 395 why-questions. For each question, the source document and one or two user-formulated answers are available in the data set. The resulting data set is of importance for our research and it will contribute to and stimulate other research in the field of why-QA. We developed a question analysis method for why-questions, based on syntactic categorization and answer type determination. The quality of the output of this module is promising for future development of our method for why-QA.