Motivating a linguistically orientated model for a conversational software agent
Kulvinder Panesar · Bradford Scholars (University of Bradford) · 2018
This paper proposes 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. We discuss the relationship between natural language processing 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, 2005a). We discuss the advantages of RRG and fitness-for-purpose for computational implementation and its level of computational adequacy (Nolan, 2004). We propose 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 (Panesar, 2017, Pokahr et al., 2014), using conceptual graphs, and resource description framework (RDF), and we highlight some implementation issues that arose at the interface between language and knowledge representation.