2127	 Natural Language Question-Answering Systems	 Recent experiments in programming natural language question-answering systems are reviewed to summarize the methods that have been developed for syntactic semantic and logical analysis of English strings. It is concluded that at least minimally effective techniques have been devised for answering questions from natural language subsets in small scale experimental systems and that a useful paradigm has evolved to guide research efforts in the field. Current approaches to semantic analysis and logical inference are seen to be effective beginnings but of questionable generality with respect either to subtle aspects of meaning or to applications over large subsets of English. Generalizing from current small-scale experiments to language-processing systems based on dictionaries with thousands of entries-with correspondingly large grammars and semantic systems-may entail a new order of complexity and require the invention and development of entirely different approaches to semantic analysis and questions answering. question-answering natural language artificial intelligence language processing fact retrieval semantics
