Paper: Learning To Tag Multilingual Texts Through Observation

ACL ID W97-0312
Title Learning To Tag Multilingual Texts Through Observation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 1997
Authors

This paper describes RoboTag, an ad- vanced prototype for a machine learning- based multilingual information extraction system. First, we describe a general client/server architecture used in learning from observation. Then we give a detailed description of our novel decision-tree tag- ging approach. RoboTag performance for the proper noun tagging task in English and Japanese is compared against human- tagged keys and to the best hand-coded pattern performance (as reported in the MUC and MET evaluation results). Re- lated work and future directions are pre- sented.