Context-Dependent Pattern Simplification by Extracting Context-Free Floating Qualifiers

Abstract

Qualification may occur anywhere within a temporal utterance. To reduce the ensuing pattern complexity for context-dependent systems such as Enguage $^{\mathrm{TM}}$, it is necessary to remove the qualified value from the utterance; rendering the utterance atemporal and presenting the value as the contextual variable when. This is possible because a qualifier—at 7:30 or until today—is immediately recognisable as such if preceding a time value: when is context-free. This appropriation gives insight into the nature of the context-dependent processing of habitual natural language. While the difference between the resultant concepts—how many coffees do I have and how old am I—is perhaps not that great despite their differing origins, this work ensures the mediation system remains practical and effective. This research is informed by a prototype for the health-tech app Memrica Prompt in support of independent living for people with early stage dementia.