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Functional linguistic based motivations for a conversational software agent
Panesar, Kulvinder
Panesar, Kulvinder
Publication Date
2019-11
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© 2019 Cambridge Scholars Publishing. Reproduced in accordance with the publisher's self-archiving policy.
Published with permission of Cambridge Scholars Publishing.
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Abstract
This chapter discusses a linguistically orientated model of a conversational software agent (CSA) (Panesar 2017) framework sensitive to natural language processing (NLP) concepts and the levels of adequacy of a functional linguistic theory (LT). We discuss the relationship between NLP and knowledge representation (KR), and connect this with the goals of a linguistic theory (Van Valin and LaPolla 1997), in particular Role and Reference Grammar (RRG) (Van Valin Jr 2005). We debate the advantages of RRG and consider its fitness and computational adequacy. We present a design of a computational model of the linking algorithm that utilises a speech act construction as a grammatical object (Nolan 2014a, Nolan 2014b) and the sub-model of belief, desire and intentions (BDI) (Rao and Georgeff 1995). This model has been successfully implemented in software, using the resource description framework (RDF), and we highlight some implementation issues that arose at the interface between language and knowledge representation (Panesar 2017).
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Accepted Manuscript
Citation
Panesar K (2019) Functional linguistic based motivations for a conversational software agent. In: Diedrichsen E and Nolan B (Eds.) Linguistic perspectives on the construction of meaning and knowledge. Cambridge: Cambridge Scholars Publishing.
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Book chapter