The paper demonstrates the possibility of deriving, from the Correlational Grammar developed solely for the purpose of automatic sentence analysis, a classification of words that could be useful in language analysis and language teaching. A group of some 90 frequent English adjectives serves as example; they are sorted into ten classes according to their behavior in strings of the type “John is easy to please,"“John is eager to please,"“John is likely to please,” etc. It is suggested that the members of a least some of these classes show common semantic features that could be used to obtain intensional definitions which would theoretically confirm the empirically derived extensional definitions supplied by correlational grammar.

Key words: Adjectives, Discourse Analysis, English, Grammar, Kernel Sentences, Phrase Structure, Semantics, Sentence Structure, Structural Analysis, Structural Grammar, Syntax

The report contains a discursive description and flow diagrams of the machine program written for a GE 425 computer in order to implement the previously developed “Multistore Procedure.” Advances in several related problem areas are reported: Classification of words in terms of “correlation indices, i.e. by means of code numbers representing the words” possibilities of forming syntatic combinations with others; Reclassification, i.e. assignation of correlation indices to word combinations; Correlator range, i.e. the extent of syntactic government – in this case of prepositions – in English sentences; Grammatical and semantic factor analysis, i.e. analysis of grammatical functions and semantic content in terms of constant factors.

Key words: machine translation, cybernetics