语法性别的最低监督归纳

Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - NAACL '03 Pub Date : 2003-05-27 DOI:10.3115/1073445.1073451

Silviu Cucerzan, David Yarowsky

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引用次数: 38

摘要

本文研究了从最小的资源开始确定语言名词的语法性别的问题:一个非常小的已知性别的种子名词列表或通过自然性别的翻译语言投射。我们表明，通过使用来自未注释语料库的上下文线索和后缀尝试建模的形态学线索的引导过程，可以对五种不同的测试语言进行准确的性别预测。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Minimally Supervised Induction of Grammatical Gender

This paper investigates the problem of determining grammatical gender for the nouns of a language starting with minimal resources: a very small list of seed nouns for which gender is known or via translingual projection of natural gender. We show that through a bootstrapping process that uses contextual clues from an unannotated corpus and morphological clues modeled with suffix tries, accurate gender predictions can be induced for five diverse test languages.

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Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - NAACL '03

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