论文标题
通过信息增益预测跨语言形容词
Predicting cross-linguistic adjective order with information gain
论文作者
论文摘要
语言在其前，之后或周围的多种形容词的位置各不相同，但是它们通常以这些形容词的相对顺序表现出强烈的语言倾向（例如，英语中的“大蓝色盒子”，“ grandeboîteBleuein French，in French，”AlsundboîteBleue'in French，以及Alsunduquq al'azrazraq alkabab alkab alkab \ frentair'inkab frention''我们基于最大化信息增益来推进跨类型赋予语言的形容词订单的新定量账户。我们的模型解决了法国型ANA序列的左右不对称方法，其方法与AAN和NAA顺序相同，而没有吸引其他机制。我们发现，在32种语言中，形容词的首选顺序在很大程度上反映了最大化信息增益的有效算法。
Languages vary in their placement of multiple 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 `alsundūq al'azraq alkab\=ır' in Arabic). We advance a new quantitative account of adjective order across typologically-distinct languages based on maximizing information gain. Our model addresses the left-right asymmetry 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 largely mirrors an efficient algorithm of maximizing information gain.
