Paper: On-Demand Information Extraction

ACL ID P06-2094
Title On-Demand Information Extraction
Venue Annual Meeting of the Association of Computational Linguistics
Session Poster Session
Year 2006
Authors

At present, adapting an Information Ex- traction system to new topics is an expen- sive and slow process, requiring some knowledge engineering for each new topic. We propose a new paradigm of Informa- tion Extraction which operates 'on demand' in response to a user's query. On-demand Information Extraction (ODIE) aims to completely eliminate the customization ef- fort. Given a user’s query, the system will automatically create patterns to extract sa- lient relations in the text of the topic, and build tables from the extracted information using paraphrase discovery technology. It relies on recent advances in pattern dis- covery, paraphrase discovery, and ex- tended named entity tagging. We report on experimental results in which the system created useful tables for many topics, demonstra...