A Rule-Based Approach To Ill-Formed Input

Though natural language understanding systems have improved markedly in recent years, they have only begun to consider a major problem of truly natural input: ill-formedness. Quite often natural language input is ill-formed in the sense of being misspelled, ungrammatical, or not entirely meaningful. A requirement for any successful natural language interface must be that the system either intelligently guesses at a user's intent, requests direct clarification, or at the very least, accurately identifies the ill-formedness. This paper presents a proposal for the proper treatment of ill-formed input. Our conjecture is that ill-formedness should be treated as rule-based. Violation of the rules of normal processing should be used to signal ill-formedness. Meta-rules modifying the rules of normal processing should be used for error identification and recovery. These meta-rules correspond to types of errors. Evidence for this conjecture is presented as well as some open ~]estions.