A modular information extraction system

  • Authors:

  • Ronen Feldman;Yizhar Regev;Maya Gorodetsky

  • Affiliations:

  • (Correspd. ronen.feldman@huji.ac.il) Information Systems Department, School of Business Administration, Hebrew University of Jerusalem, Jerusalem 91905, Israel;Information Systems Department, School of Business Administration, Hebrew University of Jerusalem, Jerusalem 91905, Israel;Information Systems Department, School of Business Administration, Hebrew University of Jerusalem, Jerusalem 91905, Israel

  • Venue:
  • Intelligent Data Analysis
  • Year:
  • 2008

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Abstract

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.