首页> 外文会议>Computer Processing of Oriental Languages: Beyond the Orient: The Research Challenges Ahead; Lecture Notes in Artificial Intelligence; 4285 >The Incremental Use of Morphological Information and Lexicalization in Data-Driven Dependency Parsing
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The Incremental Use of Morphological Information and Lexicalization in Data-Driven Dependency Parsing

机译:数据驱动的依存关系分析中形态信息和词汇化的增量使用

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Typological diversity among the natural languages of the world poses interesting challenges for the models and algorithms used in syntactic parsing. In this paper, we apply a data-driven dependency parser to Turkish, a language characterized by rich morphology and flexible constituent order, and study the effect of employing varying amounts of morpholexical information on parsing performance. The investigations show that accuracy can be improved by using representations based on inflectional groups rather than word forms, confirming eaxlier studies. In addition, lexicalization and the use of rich morphological features are found to have a positive effect. By combining all these techniques, we obtain the highest reported accuracy for parsing the Turkish Treebank.
机译:世界自然语言之间的类型多样性对句法分析中使用的模型和算法提出了有趣的挑战。在本文中,我们将数据驱动的依赖项解析器应用于土耳其语,该语言具有丰富的形态和灵活的组成顺序,并研究了采用不同数量的词法信息对解析性能的影响。调查表明,通过使用基于屈折词组而不是单词形式的表示形式可以提高准确性,这证实了更加复杂的研究。此外,发现词汇化和使用丰富的形态特征具有积极作用。通过结合所有这些技术,我们获得了解析土耳其树库的最高精度报告。

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