Paper: Unsupervised Discovery Of Scenario-Level Patterns For Information Extraction

ACL ID A00-1039
Title Unsupervised Discovery Of Scenario-Level Patterns For Information Extraction
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2000
Authors

Information Extraction (IE) systems are com- monly based on pattern matching. Adapting an IE system to a new scenario entails the construction of a new pattern base---a time- consuming and expensive process. We have implemented a system for finding patterns au- tomatically from un-annotated text. Starting with a small initial set of seed patterns proposed by the user, the system applies an incremental discovery procedure to identify new patterns. We present experiments with evaluations which show that the resulting patterns exhibit high precision and recall.