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Improving Arabic Dependency Parsing with Form-based and Functional Morphological Features

机译:改进基于表单和功能形态特征的阿拉伯语依赖性解析

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We explore the contribution of morphological features - both lexical and inflectional -to dependency parsing of Arabic, a morphologically rich language. Using controlled experiments, we find that definiteness, person, number, gender, and the undiacritzed lemma are most helpful for parsing on automatically tagged input. We further contrast the contribution of form-based and functional features, and show that functional gender and number (e.g., "broken plurals") and the related rationality feature improve over form-based features. It is the first time functional morphological features are used for Arabic NLP.
机译:我们探索了词法特征和词尾变化的形态特征对依赖分析阿拉伯语的贡献,阿拉伯语是一种形态丰富的语言。通过控制实验,我们发现确定性,人员,数量,性别和未区分词条引理对于自动标记输入的解析最有帮助。我们进一步对比了基于表单的功能和功能特征的贡献,并表明,与基于表单的功能相比,功能性别和数字(例如,“破碎的复数”)以及相关的合理性功能得到了改善。这是阿拉伯语NLP首次使用功能形态特征。

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