Hostname: page-component-76d6cb85b7-dqfph Total loading time: 0 Render date: 2026-07-14T15:40:29.583Z Has data issue: false hasContentIssue false

Quantifying relational nouns in corpora

Published online by Cambridge University Press:  20 October 2022

LELIA GLASS*
Affiliation:
School of Modern Languages Georgia Institute of Technology 613 Cherry St NW Atlanta, GA 30313 United States lelia.glass@modlangs.gatech.edu
Rights & Permissions [Opens in a new window]

Abstract

While relational nouns (cousin) are traditionally delineated in a binary and theory-dependent manner, this article approximates relationality as a continuous, objective corpus metric (Percent Possessive) – allowing for lexicon-wide exploration of which nouns are more or less relational and why. Comparing across nouns and accounting for the ontological class of the noun's referent (focusing on nouns denoting artifacts, natural kinds, occupations, humans and locations), I find that Percent Possessive is positively correlated with a noun's per-million-word frequency. Comparing across different web communities, I find that a noun is more frequent, and shows a greater ratio of definite to indefinite tokens, in the community where its Percent Possessive is significantly higher. I take these findings to be consistent with the claim that a noun is more easily interpreted as relational (as measured by Percent Possessive) when human interaction with its referent is more conventional (as measured by its frequency and definite-to-indefinite ratio). Inspired by the many authors who have suggested a socio-cultural component to relationality and possession, this article explores at scale in English how nouns reflect the conventions of the people who use them.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press
Figure 0

Figure 1. Box plot of the percentage of possessive tokens of all nouns in each ontological class adapted from WordNet, with outliers labeled

Figure 1

Figure 2. Percent Possessive correlates strongly with existing classifications of relational and non-relational nouns from NomBank and Williams

Figure 2

Table 1. Counts of possessive and non-possessive tokens of knife in both AskReddit and Cooking, along with an example of each cell. A Fisher Exact Test on this contingency table shows that knife is significantly more often possessive in Cooking than in AskReddit

Figure 3

Table 2. Nouns found in a Fisher Exact Test to be used as possessive significantly more often (p < 0.01) in a specialty subreddit compared to AskReddit (focusing only on nouns labeled as artifacts, natural kinds, humans, occupations, or locations in WordNet)

Figure 4

Figure 3. Percent Possessive as a function of log-transformed per-millon-word count in AskReddit, color-coded by ontological class

Figure 5

Figure 4. Paired visualization of the per-million-word count of the same noun in AskReddit versus in the specialty subreddit in which it is significantly more often possessive

Figure 6

Figure 5. Percent Possessive as a function of the percentage of definite versus indefinite tokens in AskReddit, color-coded by ontological class

Figure 7

Figure 6. Paired visualization of the percentage of definite tokens of the same noun in AskReddit versus in the specialty subreddit in which it is significantly more often possessive