|Title||Automatic Acquisition of Domain Knowledge for Information Extraction|
|Publication Type||Conference Paper|
|Year of Publication||2000|
|Authors||Yangarber R, Grishman R, Tapanainen P|
|Conference Name||18th International Conference on Computational Linguistics|
In developing an Information Extraction (IE) system for a new class of events or relations, one of the major tasks is identifying the many ways in which these events or relations may be expressed in text. This has generally involved the manual analysis and, in some cases, the annotation of large quantities of text involving these events. This paper presents an alternative proach, based on an automatic discovery procedure, ExDIsCO, which identifies a set of relevant documents and a set of event patterns from un-annotated text, starting from a small set of "seed patterns." We evaluate ExDISCO by comparing the performance of discovered patterns against that of manually constructed systems on actual extraction tasks.