Paper: Japanese Named Entity Recognition Based On A Simple Rule Generator And Decision Tree Learning

ACL ID P01-1041
Title Japanese Named Entity Recognition Based On A Simple Rule Generator And Decision Tree Learning
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2001
Authors
  • Hideki Isozaki (NTT Communication Science Laboratories, Kyoto Japan)

Named entity (NE) recognition is a task in which proper nouns and nu- merical information in a document are detected and classified into categories such as person, organization, location, and date. NE recognition plays an es- sential role in information extraction systems and question answering sys- tems. It is well known that hand-crafted systems with a large set of heuris- tic rules are difficult to maintain, and corpus-based statistical approaches are expected to be more robust and require less human intervention. Several statis- tical approaches have been reported in the literature. In a recent Japanese NE workshop, a maximum entropy (ME) system outperformed decision tree sys- tems and most hand-crafted systems. Here, we propose an alternative method based on a simple rule generator an...