Predicting cross-linguistic adjective order with information gain

Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 957–967 August 1–6, 2021. ©2021 Association for Computational Linguistics 957 Predicting cross-linguistic adjective order with information gain William Dyer Oracle Corporation william.dyer@oracle.com Richard Futrell University of California, Irvine rfutrell@uci.edu Zoey Liu Boston College ying.liu.5@bc.edu Gregory Scontras University of California, Irvine g.scontras@uci.edu Abstract Languages vary in their placement of multi- ple adjectives before, after, or surrounding the noun, but they typically exhibit strong intra- language tendencies on the relative order of those adjectives (e.g., the preference for ‘big blue box’ in English, ‘grande boîte bleue’ in French, and ‘als.und¯uq al’azraq alkab¯ır’ in Ara- bic). We advance a new quantitative account of adjective order across typologically-distinct languages based on maximizing information gain. Our model addresses the left-right asym- metry of French-type ANA sequences with the same approach as AAN and NAA orderings, without appeal to other mechanisms. We find that, across 32 languages, the preferred order of adjectives mirrors an efficient algorithm of maximizing information gain. 1 Introduction Languages that allow multiple sequential adjective modifiers tend to exhibit strong tendencies on the relative order of adjectives, as in ‘big blue box’ vs. ‘blue big box’ in English (Dixon, 1982). To date, most of the research on adjective ordering has focused on preferences in pre-nominal languages like English where adjectives precede the modi- fied noun (Futrell et al., 2020a), or in post-nominal languages like Arabic where adjectives follow the noun (Kachakeche and Scontras, 2020). This re- search usually posits a metric, such as informa- tion locality (Futrell et al., 2020b) or subjectivity (Scontras et al., 2017), which governs the preferred distance between a noun and its adjectives. Be- cause these theories predict only the relative linear distance between noun and adjective, they cannot be straightforwardly applied to mixed languages like French, where adjectives regularly appear both before and after the modified noun, at least not with- out added assumptions about hierarchical distance (Cinque, 1994). Instead, these mixed languages are often modeled with constraints on which adjective classes or functions can appear before or after a noun (Cinque, 2010; Fox and Thuilier, 2012). Traditional accounts of adjective ordering in the linguistics literature often assume a tree structure in which the target measure is the hierarchical dis- tance from noun (N) to adjective (A). According to syntactic accounts, ordering regularities are pre- dicted by a universal hierarchy of lexical seman- tic classes (e.g., color adjectives are hierarchically closer to the modified noun than size adjectives; Cinque, 1994; Scott, 2002). Alternative accounts use aspects of adjective meaning to predict adjec- tive order, making appeal to notions like ‘inherent- ness’ (Whorf, 1945) or ‘definiteness of denotation’ (Martin, 1969). Recently, Scontras et al. (2017) provide experimental evidence that their synthesis of semantic predictors into a continuum based on subjectivity reliably predicts ordering preference in English; followup studies have found subjectivity to be a reliable predictor in other languages as well (Tagalog: Samonte and Scontras, 2019; Mandarin: Shi and Scontras, 2020; Arabic: Kachakeche and Scontras, 2020; Spanish: Rosales Jr. …

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