The origins of word order universals: Evidence from corpus statistics and silent gesture
The origins of word order universals: Evidence from corpus statistics and silent gesture
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词序共性的起源:来自语料库统计和沉默手势的证据
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发表时间:
2018
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通讯作者:
M. Schouwstra
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作者:
S. Kirby;J. Culbertson;M. Schouwstra
Why are some patterns of noun phrase order (e.g., N-Adj-Num-Dem, ‘houses big five these’) much more common than others (e.g., N-Dem-Num-Adj, ‘houses these five big’)? An intriguing possibility is that this distribution emerges in response to a general cognitive bias favouring a transparent relationship between conceptual structure and linear order – an isomorphism bias. In conceptual structure, Adj is closest to N, then Num, then Dem (Fig. 1A). Linear orders that can be read off this nested structure are isomorphic, and these orders are the most common cross-linguistically. Previous experimental work has found an isomorphism in both traditional artificial language learning (Culbertson & Adger, 2014), and silent gesture experiments (Culbertson et al., 2016). For example, Culbertson et al. (2016) asked non-signing English speakers to communicate simple pictures using only gesture. Items were groups of 4 or 5 (Num) objects (N), either spotted or striped (Adj), in a proximal or distal location (Dem). Participants spontaneously improvised isomorphic gestures that did not reflect their native language. These results suggest that an isomorphism bias is present, however they leave open the origin of this bias. In particular, they cannot tell us the origins of the conceptual structure that word order is isomorphic to. Here we show that the conceptual structure of the noun phrase is learnable by observing simple statistics about objects in the world. Intuitively, our proposal is this: properties (~Adj) are more inherent to objects than numerosities (~Num), and location or discourse status (~Dem) is generally not an inherent feature of objects (cf. Rijkhoff 2002). More precisely, we quantify this notion using point-wise mutual information (Fig. 1B), a measure of the strength of association between pairs of elements. Using linguistic corpora as a proxy for the world, we can measure average pmi 212