rules") which represents concept hierarchy and causal relationships for an objective field. Knowledge of the objective field is used in the process to interpret input sentences as a model for the objective world. In interpreting sentences, a procedure judges preferences for interpretation candidates by identifying causal relationship with messages in the preceding context, where the causal relationship is used to supplement some shortage of information and to give either an affirmative or a negative explanation to the interpretation. The procedure has been implemented in an experimental question-answering system, whose current task is consultation in operating an electronic device. The experimental results are shown for a concrete problem involving resolving anaphoric references, and characteristics of the knowledge processing system are discussed." />

Understanding Conversational Sentences Using Multi-Paradigm World Knowledge

Teruhiko UKITA  Satoshi KINOSHITA  Kazuo SUMITA  Hiroshi SANO  Shin'ya AMANO  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E75-D   No.3   pp.352-362
Publication Date: 1992/05/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Artificial Intelligence and Cognitive Science
Keyword: 
natural language understanding,  knowledge representation,  inference,  conversation,  

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Summary: 
Resolving ambiguities in interpreting the user's utterances is one of the most fundamental problems in the development of a question-answering system. The process of disambiguating interpretations requires knowledge and inference functions on an objective task field. This paper describes a framework for understanding conversational language, using the multi-paradigm knowledge representation (frames" and rules") which represents concept hierarchy and causal relationships for an objective field. Knowledge of the objective field is used in the process to interpret input sentences as a model for the objective world. In interpreting sentences, a procedure judges preferences for interpretation candidates by identifying causal relationship with messages in the preceding context, where the causal relationship is used to supplement some shortage of information and to give either an affirmative or a negative explanation to the interpretation. The procedure has been implemented in an experimental question-answering system, whose current task is consultation in operating an electronic device. The experimental results are shown for a concrete problem involving resolving anaphoric references, and characteristics of the knowledge processing system are discussed.