Paper: Automatically Building Training Examples for Entity Extraction

ACL ID W11-0319
Title Automatically Building Training Examples for Entity Extraction
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2011
Authors

In this paper we present methods for automat- ically acquiring training examples for the task of entity extraction. Experimental evidence show that: (1) our methods compete with a current heavily supervised state-of-the-art sys- tem, within 0.04 absolute mean average pre- cision; and (2) our model significantly out- performs other supervised and unsupervised baselines by between 0.15 and 0.30 in abso- lute mean average precision.