Smart Paradigms and the Predictability and Complexity of Inflectional Morphology
Smart Paradigms and the Predictability and Complexity of Inflectional Morphology
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智能范式以及屈折形态的可预测性和复杂性
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发表时间：
2012
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通讯作者：
Aarne Ranta
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作者：
Grégoire Détrez;Aarne Ranta
形态词典通常是在形态范式的基础上实现的，对应于构建一个词的完整屈折表的不同方式。计算精确的词典可能使用数百种范式，词典编纂者很难从中进行选择。为了使这项任务自动化，本文引入了智能范式的概念。它是一个元范式，它检查基本形式并试图推断哪个低级范式适用。如果结果不确定，则会给出更多的歧视形式。平均所需的形式数是对屈折系统可预测性的衡量。系统的整体复杂性还必须考虑到范例定义本身的代码大小。本文对开源的GF资源语法库中实现的智能范式进行了评估。评估了四种不同语言的可预测性和复杂性：英语、法语、瑞典语和芬兰语。主要结果是，当形态学的复杂性增加时，可预测性不会降低，这意味着智能范式为手动构建和/或自动引导词典提供了有效的工具。
Morphological lexica are often implemented on top of morphological paradigms, corresponding to different ways of building the full inflection table of a word. Computationally precise lexica may use hundreds of paradigms, and it can be hard for a lexicographer to choose among them. To automate this task, this paper introduces the notion of a smart paradigm. It is a meta-paradigm, which inspects the base form and tries to infer which low-level paradigm applies. If the result is uncertain, more forms are given for discrimination. The number of forms needed in average is a measure of predictability of an inflection system. The overall complexity of the system also has to take into account the code size of the paradigms definition itself. This paper evaluates the smart paradigms implemented in the open-source GF Resource Grammar Library. Predictability and complexity are estimated for four different languages: English, French, Swedish, and Finnish. The main result is that predictability does not decrease when the complexity of morphology grows, which means that smart paradigms provide an efficient tool for the manual construction and/or automatically bootstrapping of lexica.