Paper: Template-Based Information Extraction without the Templates

ACL ID P11-1098
Title Template-Based Information Extraction without the Templates
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011
Authors

Standard algorithms for template-based in- formation extraction (IE) require predefined template schemas, and often labeled data, to learn to extract their slot fillers (e.g., an embassy is the Target of a Bombing tem- plate). This paper describes an approach to template-based IE that removes this require- ment and performs extraction without know- ing the template structure in advance. Our al- gorithm instead learns the template structure automatically from raw text, inducing tem- plate schemas as sets of linked events (e.g., bombings include detonate, set off, and de- stroy events) associated with semantic roles. We also solve the standard IE task, using the induced syntactic patterns to extract role fillers from specific documents. We evaluate on the MUC-4 terrorism dataset and show tha...