Selecting tense, aspect, and connecting words in language generation

Abstract

Generating language that reflects the temporal organization of represented knowledge requires a language generation model that integrates contemporary theories of tense and aspect, temporal representations, and methods to plan text. This paper presents a model that produces complex sentences that reflect temporal relations present in underlying temporal concepts. The main result of this work is the successful application of constrained linguistic theories of tense and aspect to a generator which produces meaningful event combinations and selects appropriate connecting words that relate them

    Similar works