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A Computational Model for the Linguistic Notion of Morphological Paradigm

机译:形态学范式的语言概念的计算模型

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In supervised learning of morphological patterns, the strategy of generalizing inflectional tables into more abstract paradigms through alignment of the longest common subsequence found in an inflection table has been proposed as an efficient method to deduce the inflectional behavior of unseen word forms. In this paper, we extend this notion of morphological 'paradigm' from earlier work and provide a formalization that more accurately matches linguist intuitions about what an inflectional paradigm is. Additionally, we propose and evaluate a mechanism for learning full human-readable paradigm specifications from incomplete data-a scenario when we only have access to a few inflected forms for each lexeme, and want to reconstruct the missing inflections as well as generalize and group the witnessed patterns into a model of more abstract paradigmatic behavior of lexemes.
机译:在形态学模式的监督学习中,已提出通过对齐在拐点表中找到的最长公共子序列来将拐点表归纳为更抽象的范例的策略,作为推论未见单词形式的拐点行为的有效方法。在本文中,我们从早期的工作中扩展了形态学“范式”的概念,并提供了一种形式化的方法,可以更准确地匹配语言学家对屈折范式的理解。此外,我们提出并评估了一种从不完整数据中学习完整的人类可读范式规范的机制-一种情况,当我们只能访问每个词素的几种变形形式,并希望重构缺失的变形并归纳和分组时,目击的模式转化为词素更抽象的范式行为模型。

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