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- W17638407 abstract "This chapter reviews five aspects of a full-scale story comprehension model. It highlights the main issues of full-scale story comprehension model architecture: (1) language analysis is best done by collections of relatively autonomous word sense experts who are assembled together on demand from each input utterance or sentence, (2) meaning representation for a inferentially complex tasks is best done using a compressionist technique, (3) reference, and specifically referent creation, should be an active process that passes each newly created token through a hierarchy of pattern matching, (4) building and maintaining personality models of the characters in the story, and two-character relationship models between each pair of characters is vital for inference and prediction conditioning, and (5) prediction fulfillment must be based on a sink pattern matching paradigm, which actively rescans the prediction set each time a new fact or belief enters the model or is generated by the model's inferential component." @default.
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- W17638407 date "1979-01-01" @default.
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- W17638407 title "FIVE ASPECTS OF A FULL-SCALE STORY COMPREHENSION MODEL" @default.
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- W17638407 doi "https://doi.org/10.1016/b978-0-12-256380-5.50020-7" @default.
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