Automatic Extraction of Morphological Lexicons from Morphologically Annotated Corpora

Automatic Extraction of Morphological Lexicons from Morphologically Annotated Corpora
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从形态标注语料库中自动提取形态词典

DOI：
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发表时间：
2013
期刊：
Conference on Empirical Methods in Natural Language Processing
影响因子：
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通讯作者：
Owen Rambow
Owen Rambow
中科院分区：
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文献类型：
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作者：
R. Eskander;Nizar Habash;Owen Rambow

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提出了一种从形态标注语料库中自动学习屈折类和相关引理的方法。该方法由一个与核心语言无关的算法组成，该算法可以针对特定语言进行优化。该方法在埃及阿拉伯语和德语这两种形态丰富的语言上进行了验证。我们对埃及阿拉伯语的最佳方法在简单基线上误差降低了55.6%；我们对德语的最佳方法误差降低了66.7%。
We present a method for automatically learning inflectional classes and associated lemmas from morphologically annotated corpora. The method consists of a core languageindependent algorithm, which can be optimized for specific languages. The method is demonstrated on Egyptian Arabic and German, two morphologically rich languages. Our best method for Egyptian Arabic provides an error reduction of 55.6% over a simple baseline; our best method for German achieves a 66.7% error reduction.