What determines the order of adjectives in English? Comparing efficiency-based theories using dependency treebanks

What determines the order of adjectives in English? Comparing efficiency-based theories using dependency treebanks
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英语形容词的顺序是由什么决定的?

DOI:
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发表时间:
2020
期刊:
Annual Meeting of the Association for Computational Linguistics
影响因子:
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通讯作者:
Gregory Scontras
Gregory Scontras
中科院分区:
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文献类型:
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作者:
Richard Futrell;William Dyer;Gregory Scontras

文献摘要

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我们探讨的科学问题是,是什么决定了英语中形容词的优先顺序,比如在“big blue box”这样的短语中,多个形容词修饰后面的名词。我们实施并测试了四个定量理论,所有这些理论都是在人类语言生产和理解效率方面的理论动机。我们测试的四个理论是主观性(Scontras et al., 2017)、信息局域性(Futrell, 2019)、集成成本(Dyer, 2017)和信息增益(我们引入)。我们根据理论在手动解析和自动解析依赖树库中预测未见形容词顺序的能力来评估理论。我们发现主观性、信息局部性和信息增益都是强有力的预测因子,有证据表明存在双因素,其中主观性和信息增益反映了涉及语义的因素,而信息局部性反映了搭配偏好。
We take up the scientific question of what determines the preferred order of adjectives in English, in phrases such as big blue box where multiple adjectives modify a following noun. We implement and test four quantitative theories, all of which are theoretically motivated in terms of efficiency in human language production and comprehension. The four theories we test are subjectivity (Scontras et al., 2017), information locality (Futrell, 2019), integration cost (Dyer, 2017), and information gain, which we introduce. We evaluate theories based on their ability to predict orders of unseen adjectives in hand-parsed and automatically-parsed dependency treebanks. We find that subjectivity, information locality, and information gain are all strong predictors, with some evidence for a two-factor account, where subjectivity and information gain reflect a factor involving semantics, and information locality reflects collocational preferences.