基于树库转换的藏语依存句法树库构建方法

构建藏语依存树库是实现藏语句法分析的重要基础，对藏语本体研究和信息处理具有重要价值。基于此，该文提出了一种基于树库转换的藏语依存树库构建方法。该方法首先扩充了前期构建的藏语短语结构树库，然后根据藏语短语结构树和依存树的特征设计树库转换规则，实现藏语短语结构树到依存结构树的初步转换，最后对自动转换结果进行人工校验，得到了2.2万句藏语依存树。为了对转换结果做出量化评价，该文抽取了依存树库中5%的依存树，对其依存关系进行校验和统计，最终依存关系的准确率达到89.36%,中心词的准确率达到92.09%。此外，该文使用基于神经网络的句法分析模型验证了依存树库的有效性。在该模型上，UAS值和LAS值分别达到83.62%和81.90%。研究证明，使用半自动的树库转换方法能够有效地完成藏语依存树库构建工作。

Construction of the Tibetan Dependency Treebank Based on Treebank Conversion

The construction of the Tibetan Dependency Treebank is a fundamental task for subsequent technology development. This paper proposes a method for constructing a Tibetan Dependency Treebank based on treebank conversion. First, the existing Tibetan Phrase Structure Treebank is expanded. Then, treebank conversion rules are designed based on the characteristics of the Tibetan phrase structure tree and the dependency tree. Finally, the automatic conversion result is proofread manually, achieving 22,000 Tibetan dependency trees. This paper extracts 5% of the sentences in the dependency treebank, and the accuracy rate of the dependency relationship of the final sample reached 89.36%, and the head word reached 92.09%. A neural network-based dependency parsing model trained by the treebank achieves 83.62% UAS and 81.90% LAS.