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The generation of temporal expressions in natural language
Abstract
Until now, the problem of generating natural language texts which contain temporal expressions has been largely ignored, with treatments extending at best only to tense. In particular, temporal adverbials have not been incorporated, even though they represent the second most common way of expressing temporal relations in natural language. This work proposes a treatment of temporal adverbials, concentrating on prepositional phrases, which integrates well with schemes for generating tense, and is based on four assertions: (1) Planning temporal prepositional phrases requires reference to common-sense knowledge) (2) Generation of natural language is best achieved through the use of hierarchical constraint propagation. (3) Lexical selection of a single item requires the use of multiple sources of constraints. (4) In contradistinction to other proposals, it is asserted that tense and multiple temporal adverbials describing the same event are derived from a common data source. This treatment not only ensures the principled generation of correct temporal prepositional phrases, but enables the simultaneous specification of tense and multiple temporal adverbials. In addition, it establishes the origins of different temporal expressions in relation to client data, defines the correspondence of temporal data to their expression in language terms, and defines the duties of the semantic component of a natural language generator and the duties of the program requesting the generation (the client). Furthermore, the generation of temporal expressions serves as an additional test for current temporal representation schemes, one which is expected to indicate inadequacies in them and point the way to better mechanisms.
Subject Area
Computer science|Artificial intelligence
Recommended Citation
Forster, David Robson, "The generation of temporal expressions in natural language" (1991). Doctoral Dissertations Available from Proquest. AAI9120877.
https://scholarworks.umass.edu/dissertations/AAI9120877