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This paper describes the use of an on-line system to do word-sense ambiguity resolution and content analysis of English paragraphs, using a system of semantic analysis programmed in Q32 LISP 1.5. The system of semantic analysis comprises dictionary codings for the text words, coded forms of permitted message, and rules producing message forms in combination on the basis of a criterion of semantic closeness. All these can be expressed as a single system of rules of phrase-structure form. In certain circumstances the system is able to enlarge its own dictionary in a real-time mode on the basis of information gained. | Mechanical Translation and Computational Linguistics vol.11 nos. 1 and 2 March and June 1968 On-Line Semantic Analysis of English Texts by Yorick Wilks Pembroke College Cambridge This paper describes the use of an on-line system to do word-sense ambiguity resolution and content analysis of English paragraphs using a system of semantic analysis programmed in Q32 LISP 1.5. The system of semantic analysis comprises dictionary codings for the text words coded forms of permitted message and rules producing message forms in combination on the basis of a criterion of semantic closeness. All these can be expressed as a single system of rules of phrase-structure form. In certain circumstances the system is able to enlarge its own dictionary in a real-time mode on the basis of information gained from the actual texts analyzed. 1. Introduction In this paper I describe a system for the on-line semantic analysis of texts up to paragraph length. It was programmed and applied in Q32 LISP 1.5 to material of two sorts newspaper editorials and passages of philosophical argument. The immediate purpose of the analysis was to resolve the word-sense ambiguity of the texts to tag each word occurrence in the texts to one and only one of its possible senses or meanings and to do so in such a way that anyone could judge the output s success or failure without knowing the coding system. The system analyzes text up to paragraph length since I follow a working hypothesis that many wordsense ambiguities cannot be resolved within the bounds of the conventional text sentence there simply isn t enough context available. So for example if someone reads in British English at least I ll have to take this post after all then he does not know without more context whether he is reading about an employment situation or one concerned with the purchase of gardening equipment. If that sentence were analyzed by any ambiguity resolution system as part of a larger text we would expect as a report on the word
