From the world to word order: the link between conceptual structure and language

Abstract

The world’s languages exhibit striking diversity. At the same time, recurring linguistic patterns suggest the possibility that this diversity is shaped by features of human cognition. One well-studied example is word order in complex noun phrases (like 'these two red vases'). While many orders of these elements are possible, a subset appear to be preferred. It has been argued that this order reflects a single underlying representation of noun phrase structure, from which preferred orders are straightforwardly derived (e.g., Cinque, 2005). Building on previous experimental evidence using artificial language learning, we show that these preferred orders arise not only in existing languages, but also in improvised sequences of gestures produced by English speakers. We then use corpus data from a wide range of languages to argue that the hypothesized underlying structure of the noun phrase might be learnable from statistical features relating objects and their properties conceptually. Using an information-theoretic measure of strength of association, we find that adjectival properties (e.g. 'red') are on average more closely related to the objects they modify (e.g. 'wine'), than numerosities (e.g. 'two'), which are in turn more closely related to the objects they modify than demonstratives (e.g., 'this'). It is exactly those orders which transparently reflect this—by placing adjectives closest to the noun, and demonstratives farthest away—which are more common across languages, and preferred in our silent gesture experiments. These results suggest that our experience with objects in the world, combined with a preference for transparent mappings from conceptual structure to linear order, can explain constraints on noun phrase order.

Learning and the typology of word order: a model of the Final-over-Final Condition

“…Leftward movement 12 Potentially this hidden structure could also be taken as something that is learned prior to the slice of learning examined here. How the underlying form would be learned prior to the word order is unclear, but one possibility is that it could be tied to the conceptual strength of association between worlds, along the lines of Culbertson et al (2019) does not create additional weakly-equivalent languages for the final-over-initial pattern, as no leftward movement applied after those in the minimal derivations is string vacuous. Any additional movement applied to a final-over-initial structure results in a different word order.…”

Examining the Inductive Bias of Neural Language Models with Artificial Languages

“…All word orders are not equally common among natural languages, and it is inter-esting to consider whether the word orders that these models are able to model more successfully are those which are more commonly seen in natural language. Some have speculated that the skew of word orders in human languages could possibly be reflective of human cognitive biases (Culbertson et al, 2012(Culbertson et al, , 2019, so it would be interesting to see to what extent the inductive biases of these models reflects this skew. Since LSTMs appear to show no preference for any word order over the others, they are clearly not reflective of attested tendencies in word order.…”