The exponential distribution of the order of demonstrative, numeral, adjective and noun

The frequency of the preferred order for a noun phrase formed by demonstrative, numeral, adjective and noun has received significant attention over the last two decades. We investigate the actual distribution of the 24 possible orders. There is no consensus on whether it is well-fitted by an exponen...

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Detalles Bibliográficos
Autor: Ferrer Cancho, Ramon|||0000-0002-7820-923X
Tipo de recurso: artículo
Fecha de publicación:2026
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:dnet:upcommonspor::08fb4b8ee32a3550f7ed5f97bdb73ef5
Acceso en línea:https://hdl.handle.net/2117/461788
https://dx.doi.org/10.1080/09296174.2026.2617705
Access Level:acceso embargado
Palabra clave:Noun phrase
Exponential distribution
Power law distribution
Word order
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Llenguatge natural
Descripción
Sumario:The frequency of the preferred order for a noun phrase formed by demonstrative, numeral, adjective and noun has received significant attention over the last two decades. We investigate the actual distribution of the 24 possible orders. There is no consensus on whether it is well-fitted by an exponential or a power law distribution. We find that an exponential distribution is a much better model. This finding and other circumstances where an exponential-like distribution is found challenge the view that power-law distributions, e.g. Zipf’s law for word frequencies, are inevitable. We also investigate which of two exponential distributions gives a better fit: an exponential model where the 24 orders have non-zero probability (a geometric distribution truncated at rank 24) or an exponential model where the number of orders that can have non-zero probability is variable (a right-truncated geometric distribution). When consistency and generalizability are prioritized, we find higher support for the exponential model, where all 24 orders have non-zero probability. These findings strongly suggest that there is no hard constraint on word order variation, and then unattested orders merely result from undersampling, consistently with Cysouw’s view.