A SUBLANGUAGE APPROACH TO NATURAL-LANGUAGE PROCESSING FOR AN EXPERT-SYSTEM

A sublanguage grammar approach with strong reliance on semantic word classes was used to develop an NLP component for processing the free-text comments on life insurance applications for evaluation by an underwriting expert system. The NLP component is implemented using a logic-programming formalism. Lexicon entries contain semantic word class tags such as BODYPART, SYMPTOM, or MEDICATION. Adjacency Rules and an Ambiguity Filter are used to interpret the input data using these semantic word classes. Across two experiments, the system produced appropriate readings for 96.8% of a sample of 2069 utterances, and the number of parses produced per utterance was 1.079 for the same sample. Misspellings caused the system its only serious problem. The sublanguage approach to processing text was shown to be very promising for expert systems and suggests itself as a useful paradigm for a range of other text-based systems which must deal with naturally occurring and frequently ungrammatical texts.