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Language Generation for Broad-Coverage, Explainable Cognitive Systems (2201.10422v1)
Published 25 Jan 2022 in cs.CL and cs.AI
Abstract: This paper describes recent progress on natural language generation (NLG) for language-endowed intelligent agents (LEIAs) developed within the OntoAgent cognitive architecture. The approach draws heavily from past work on natural language understanding in this paradigm: it uses the same knowledge bases, theory of computational linguistics, agent architecture, and methodology of developing broad-coverage capabilities over time while still supporting near-term applications.