A modular information extraction system

Ronen Feldman*, Yizhar Regev, Maya Gorodetsky

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


In today's information age, the amount of text documents available electronically (on the Web, on corporate intranets, on news wires and elsewhere) is overwhelming. Search engines and information retrieval, while useful to find documents that satisfy a certain query, offer little help with analyzing the unstructured documents themselves. Text Mining is the automated process of analyzing unstructured, natural language text in order to discover information and knowledge that are difficult to retrieve. Information Extraction (IE) centers on finding entities and relations in free text and provides a solid foundation for text mining. In this paper we present a modular IE system, based on the DIAL language. DIAL allows users to implement IE solutions for various domains rapidly, based on a common Natural Language Processing (NLP) infrastructure. We demonstrate in detail an implementation of a system for extracting relations in the intelligence news domain. We present an evaluation of our system and discuss enhancements for other domains, such as emails.

Original languageAmerican English
Pages (from-to)51-71
Number of pages21
JournalIntelligent Data Analysis
Issue number1
StatePublished - 2008


  • Information extraction
  • Natural language processing
  • Text mining applications


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