Abstract
We introduce a computationally tractable model for language generation based on the Meaning-Text Theory of Mel’cuk et al., in which the lexicon plays a central role. To illustrate the descriptive scope and paraphrase capabilities of the model, we show how the lexicon influences the set of choices at four different points during the multi-stage realization process: (1) semantic net simplification, (2) determination of root lexical node for the deep syntactic dependency tree, (3) possible application of deep paraphrase rules using lexical functions, and (4) surface syntactic realization. We also show some of the ways in which the theme/rheme specifications within the semantic net influence lexical and syntactic choices during realization. Examples are taken primarily from an implemented system which generates paragraph-length reports about the usage of operating systems.
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Iordanskaja, L., Kittredge, R., Polguère, A. (1991). Lexical Selection and Paraphrase in a Meaning-Text Generation Model. In: Paris, C.L., Swartout, W.R., Mann, W.C. (eds) Natural Language Generation in Artificial Intelligence and Computational Linguistics. The Kluwer International Series in Engineering and Computer Science, vol 119. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-5945-7_11
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DOI: https://doi.org/10.1007/978-1-4757-5945-7_11
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