An Explanation Facility for a Grammar Writing System

Explanation has become a standard feature in many expert systems today. Adapting from this work, a study was made to determine the types of explanation required in a grammar writing system and to investigate design and iimplementation issues. The first version of this explanation facility is based on a derivational history of the inferencing process, and although no supplementary knowledge is used, this explanation facility is able to furnish answers to the traditional why, how and what type of queries, and even the what-if (simulation) query. The explanation is also enhanced through the use of special files containing canned-text for describing grammar rules and variables. ~1. In t roduc t ion Explanation for expert systems has been studied very extensively, and has become a ~tandard feature in these systems. Its objectives are to enable users to understand how conclusions are reached, to be convinced t:hat these conclusions are reasonable, and to debug the knowledge base and possibly problem solving behavior as well. Viewed in a more general context, research into explanation is an essential component of the study into the symbiosis between man and machine, supported by the empirical fact that most knowledge-based systems are intended to assist human endeavor and are almost never intended to be autonomous agents. Grammar writing systems (GWS) used in Natural Language Processing (NLP) work have been compared to expert systems (Boitet and Gerber, 1984) by equating the knowledge base to the grammar, and the problem-solving activity to the transformation performed on the text representation structure. Existing GWSs do not provide any explanation because their usage is usually confined to expert users who can understand low-level programs or rule traces, and moreover, the inferencing process for NLP applications is normally carried out in batch mode. If users do interact with the system, it is usually for the purpose of resolving ambiguities (for example), which is obviously quite different from explanation. The presence of explanation is one of the main reason why expert systems have found a substantial degree of success with users, so perhaps NLP systems could also benefit from such a service, especially in gaining end-user acceptance. In this investigation, we are not studying the nature of explanation per se, but rather, starting from an existing system, determine what explanations can be provided and how. The system under consideration is the GWS associated with a machine translation environment known as JEMAH (Tong, 1988; 1989). Previous studies on explanation (see, for e x a m p l e , S w a r t o u t , 1984, and Chandrasekharan, 1989) have shown that providing effective explanation frequently requires supplementary knowledge in addition to the existing knowledge base. For example, the metamorphosis f r o m MYCIN to NEOMYCIN (Clancey, 1983) requires the addition of meta-rules to explicitly represent the diagnostic strategy and the relationship between rules. The research described in this paper will ascertain the level and degree of explanation which can be provided without resorting to the use of supplementary knowledge, more or less along the same lines as Wick and Slagle (1989), who studied the type of explanation facility that can be provided based on current expert system methodo log ies where supplementary knowledge is not available. Besides the knowledge content required for such explanation, the other side issues related