(Redirected from Crystal)
- AKA: Crystal.
- The system was demonstrated on automatically creating a weak ontology about diagnoses by examining patient medical records.
- See: Information Extraction;
- (Soderland et al., 1995) ⇒ Stephen Soderland, David Fisher, Jonathan Aseltine, and Wendy G. Lehnert. (1995). “CRYSTAL: Inducing a Conceptual Dictionary.” In: Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI 1995).
- 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.