CRYSTAL: Inducing a Conceptual Dictionary
Abstract
One of the central knowledge sources of an information extraction system is a dictionary of linguistic patterns that can be used to identify the conceptual content of a text. 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.
Cite
Text
Soderland et al. "CRYSTAL: Inducing a Conceptual Dictionary." International Joint Conference on Artificial Intelligence, 1995.Markdown
[Soderland et al. "CRYSTAL: Inducing a Conceptual Dictionary." International Joint Conference on Artificial Intelligence, 1995.](https://mlanthology.org/ijcai/1995/soderland1995ijcai-crystal/)BibTeX
@inproceedings{soderland1995ijcai-crystal,
title = {{CRYSTAL: Inducing a Conceptual Dictionary}},
author = {Soderland, Stephen and Fisher, David and Aseltine, Jonathan and Lehnert, Wendy G.},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1995},
pages = {1314-1321},
url = {https://mlanthology.org/ijcai/1995/soderland1995ijcai-crystal/}
}