---
title: "CRYSTAL: Inducing a Conceptual Dictionary"
authors:
  - "Stephen Soderland"
  - "David Fisher"
  - "Jonathan Aseltine"
  - "Wendy G. Lehnert"
doi: ""
url: "https://ijcai.org/proceedings/1995/169"
pdf: "https://ijcai.org/proceedings/1995/0169.pdf"
venue: "Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence"
year: 1995
pages: "1314-1320"
track: "Natural Language"
keywords:
---

# CRYSTAL: Inducing a Conceptual Dictionary

Stephen Soderland, David Fisher, Jonathan Aseltine, Wendy G. Lehnert

*Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence*, pages 1314-1320.

## Abstract

One of the central knowledge sources of an information extraction (IE) system is a dictionary of linguistic patterns that can be used to identify references to relevant information in a text. Automatic creation of conceptual dictionaries is important for portability and scalability of an IE system. This paper describes CRYSTAL, a system which automatically induces a dictionary of "concept-node definitions" sufficient to identify relevant information from a training corpus. Each of these concept-node definitions is generalized as far as possible without producing errors, so that a minimum number of dictionary entries cover the positive training instances. Because it tests the accuracy of each proposed definition, CRYSTAL can often surpass human intuitions in creating reliable extraction rules.