Abstract
Automatic Text Generation (ATG) is a Natural Language Processing (NLP) task that aims at writing acceptable and grammatical written text exploiting machine-representation systems, such as for instance knowledge bases, taxonomies and ontologies. In this sense, it is possible to state that an ATG system works like a translator that converts data into a natural-language written representation. The methods to produce the final texts may differ from those used by compilers, due to the inherent expressivity of natural languages.
ATG is not a recent discipline, even if commercial ATG technology has only recently become widely available. Today, many software environments cope with ATG, as Text Spinner, DKB Lettere, or textOmatic*Composer, just to mention a few.
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Notes
- 1.
The term comes from the Latin grammar, and indicates the norms that regulate the concordance of the tenses in the text sentences linked to the main proposition by a relationship of contemporaneity, anteriority or posteriority.
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Monteleone, M. (2020). Automatic Text Generation: How to Write the Plot of a Novel with NooJ. In: Fehri, H., Mesfar, S., Silberztein, M. (eds) Formalizing Natural Languages with NooJ 2019 and Its Natural Language Processing Applications. NooJ 2019. Communications in Computer and Information Science, vol 1153. Springer, Cham. https://doi.org/10.1007/978-3-030-38833-1_12
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