Paper: Refining Event Extraction through Cross-Document Inference

ACL ID P08-1030
Title Refining Event Extraction through Cross-Document Inference
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008
Authors

We apply the hypothesis of “One Sense Per Discourse” (Yarowsky, 1995) to information extraction (IE), and extend the scope of “dis- course” from one single document to a cluster of topically-related documents. We employ a similar approach to propagate consistent event arguments across sentences and documents. Combining global evidence from related doc- uments with local decisions, we design a sim- ple scheme to conduct cross-document inference for improving the ACE event ex- traction task 1 . Without using any additional labeled data this new approach obtained 7.6% higher F-Measure in trigger labeling and 6% higher F-Measure in argument labeling over a state-of-the-art IE system which extracts events independently for each sentence.