Cross-document event extraction and tracking: Task, evaluation, techniques and challenges

Heng Ji, Ralph Grishman, Zheng Chen, Prashant Gupta

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper proposes a new task of cross-document event extraction and tracking and its evaluation metrics. We identify important person entities which are frequently involved in events as 'centroid entities'. Then we link the events involving the same centroid entity along a time line. We also present a system performing this task and our current approaches to address the main research challenges. We demonstrate that global inference from background knowledge and cross-document event aggregation are crucial to enhance the performance. This new task defines several extensions to the traditional single-document Information Extraction paradigm beyond 'slot filling'.

Original languageEnglish (US)
Pages (from-to)166-172
Number of pages7
JournalInternational Conference Recent Advances in Natural Language Processing, RANLP
StatePublished - 2009
Externally publishedYes
EventInternational Conference on Recent Advances in Natural Language Processing, RANLP-2009 - Borovets, Bulgaria
Duration: Sep 14 2009Sep 16 2009

Keywords

  • Cross-document extraction
  • Event
  • Information extraction

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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