Learning to Tag Multilingual Texts Through Observation

Abstract

This paper describes RoboTag, an advanced prototype for a machine learningbased 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 tagging approach. RoboTag performance for the proper noun tagging task in English and Japanese is compared against humantagged keys and to the best hand-coded pattern performance (as reported in the MUC and MET evaluation results). Related work and future directions are presented. 1