Building natural language generation systems
Building natural language generation systems
Snowball: extracting relations from large plain-text collections
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Context and Page Analysis for Improved Web Search
IEEE Internet Computing
QUANTUM: A Function-Based Question Answering System
AI '02 Proceedings of the 15th Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Information extraction with term frequencies
HLT '01 Proceedings of the first international conference on Human language technology research
The role of lexico-semantic feedback in open-domain textual question-answering
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
An analysis of the AskMSR question-answering system
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Improving the performance of question answering with semantically equivalent answer patterns
Data & Knowledge Engineering
Automatic acquisition of semantic-based question reformulations for question answering
CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
Using semantic constraints to improve question answering
NLDB'06 Proceedings of the 11th international conference on Applications of Natural Language to Information Systems
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In this paper, we describe our experimentations in evaluating answer formulation for question-answering (QA) systems. In the context of QA, answer formulation can serve two purposes: improving answer extraction or improving human-computer interaction (HCI). Each purpose has different precision/recall requirements. We present our experiments for both purposes and argue that formulations of better grammatical quality are beneficial for both answer extraction and HCI.