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Natural Language Processing: many questions, no answers

Computational Linguistics, as a subfield of Linguistics, or Natural Language Processing (NLP), as a subfield of Artificial Intelligence (two research areas that nowadays can be safely considered as merged) concentrate on the “study of computer systems for understanding and generating natural language” [10], in order to develop “a computational theory of language, using the notions of algorithms and data structures from Computer Science” [2]. Typical problems for these research fields are [2]: How is the structure of sentences identified? How can knowledge and reasoning be modelled? How can language be used to accomplish specific tasks? In more recent times, these problems are being studied not so much from the traditional linguistic viewpoint (syntax and semantics) but with a focus on problems of belief models, planning processes, and functional properties of both discourse and text. I will focus my discussion on three problems in NLP. The choice of the problems to address is admittedly biased by my personal research interests, but I do believe that these problems in particular can (and should) most benefit from considerations coming from the Argumentation theory field. This paper is merely an attempt to build up a canvas of issues, on which further discussion is needed.