This results in a concept set in which the concepts are semantically related to the initial query. Terms not found in the UMLS are not excluded from the expansion process. That would limit the vocabulary to the Metathesaurus lexicon, which is not a substitute for a complete lexicon. During the last step, all concepts that are retained are re-ordered based on their Concept Space weights, and the most relevant subset is selected. More specifically, classes are made up of particular entity types.
Boundary identification represents the word-level analysis of the textual data.
The finite state lexical lookup and entity assignment systems view the data from a phrase-level representation. Since entities names do not follow a particular grammatical pattern such as noun phrases, it is not possible to rely on a fixed set of grammar patterns in order to identify phrase boundaries. Instead, a combination of word feature information is used along with some simple heuristics. Part-of speech patterns are generated using a tagged corpus rather than relying on a fixed set. As long as a tagged corpus exists where entities are identified, phrase patterns can be automatically extracted and updated by the system.