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Meaning Relations, Syntax, and Understanding

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Abstract

This paper revisits the conception of intelligence and understanding as embodied in the Turing Test. It argues that a simple system of meaning relations drawn from words/lexical items in a natural language and framed in terms of syntax-free relations in linguistic texts can help ground linguistic inferences in a manner that can be taken to be 'understanding' in a mechanized system. Understanding in this case is a matter of running through the relevant inferences meaning relations allow for, and some of these inferences are plain deductions and some can serve to act as abductions. Understanding in terms of meaning relations also supervenes on linguistic syntax because such understanding cannot be simply reduced to syntactic relations. The current approach to meaning and understanding thus shows that this is one way, if not the only way, of (re)framing Alan Turing's original insight into the nature of thinking in computing systems.

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Notes

  1. Exploring the validity or, for that matter, invalidity of the Turing Test is not the goal of this paper, and hence that question is outside the scope of the present discussion. We may note, however, that the Turing Test has targeted the understanding of natural language rather than some other cognitive task as the marker of thinking. This is what seems very relevant to the reformulation of the Turing Test in terms of the capacity to construct meaning relations to be discussed in the next section.

  2. This contrasts with the familiar hypothesis that lexical items are the atomic elements that can be shared among humans, other animals and perhaps machines, whereas the structures built out of lexical items crossing the boundary between lexical items and other functional items (for example, prepositions, tense markers) are unique to humans (see Miyagawa et al. 2014). It needs to recognized that lexical items, when taken to be atomic elements as part of a formal system, are actually conceptually empty minimal items in their formal characterization. This allows lexical items to be shared among humans and other organisms, but keeps the structures built from them from being so shared.

  3. Note that this notion of relation is way different from the relations that can be constructed, as in model-theoretic syntax, for nodes in a tree (such as precedence or dominance relations) and for categories such as NP (Noun Phrase), VP (Verb Phrase), S (Sentence) etc. which are properties of nodes (see for details, Pullum (2013)). In fact, the relations R1, … ,Rk, Rk+1, … , R∞ encompass many dimensions (such as string adjacency, precedence, dominance and parent-of relations etc.) in terms of which linguistic constructions can be characterized.

  4. Significantly, this account has differences from frame semantics (Fillmore 1976) or scripts (Schank and Abelson 1977) because the approach here is much more granular. For instance, a meaning relation between ‘a’ and ‘river’ in ‘a beautifully painted picture of the river’ cannot be easily captured by a syntactic unit or by a frame (or by a script), say, 'being a river' which will end up mapping the whole noun phrase and its grammatical function to the frame but 'a' and 'river' in are actually discontinuous frame elements (or script elements). Besides, frames may themselves participate in compositional operations in a construction through inheritance of information from daughter signs in local trees to mother signs (see Sag 2012).

  5. It may also be observed that the freely variable structures even in idioms such as 'take (something) for granted' or 'cut (something) to the bone' (with the freely variable parts underlined) are not illicit syntactic categories or units (as they are all NPs), while the fixed expressions may be productively illicit in the language ('for granted' is possible, but 'for accepted' is probably not).

  6. Croft shows that a language such as Kilivila has a fixed order of NPs after a verb, and hence their relations to each other do not help decipher the syntactic roles of the arguments. Rather, the syntactic roles of the arguments are mapped onto their participant roles.

  7. It is plausible that the probabilistic character of abductions may be compatible with Bayesian reasoning (see Lipton 2004; McCain and Poston 2014), but that is something which is outside the scope of this paper.

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Acknowledgements

I’m grateful to the anonymous reviewer and the editor for their insightful comments on the article, and for their judicious assessment of the argumentation deployed in the article.

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  1. Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana, 502285, India

    Prakash Mondal

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Mondal, P. Meaning Relations, Syntax, and Understanding. Axiomathes 32, 459–475 (2022). https://doi.org/10.1007/s10516-021-09534-x

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