Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Question terminology and representation for question type classification
COMPUTERM '02 COLING-02 on COMPUTERM 2002: second international workshop on computational terminology - Volume 14
Interrogative reformulation patterns and acquisition of question paraphrases
PARAPHRASE '03 Proceedings of the second international workshop on Paraphrasing - Volume 16
Enhanced answer type inference from questions using sequential models
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Structure Analysis and Computation-Based Chinese Question Classification
ALPIT '07 Proceedings of the Sixth International Conference on Advanced Language Processing and Web Information Technology (ALPIT 2007)
A natural language approach to content-based video indexing and retrieval for interactive e-learning
IEEE Transactions on Multimedia
Hi-index | 0.00 |
Question type (or answer type) classification is the task of determining the correct type of the answer expected to a given query. This is often done by defining or discovering syntactic patterns that represent the structure of typical queries of each type, and classify a given query according to which pattern they satisfy. In this paper, we combine the idea of using informer spans as patterns with our own part-of-speech hierarchy in order to propose both a new approach to pattern-based question type classification and a new way of discovering the informers to be used as patterns. We show experimentally that using our part-of-speech hierarchy greatly improves type classification results, and allows our system to learn valid new informers.