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Evaluation of automatic hypernym extraction from technical corpora in English and Dutch

机译:英语和荷兰语技术语料库中自动上提法的提取评价

摘要

In this research, we evaluate different approaches for the automatic extraction of hypernym relations from English and Dutch technical text. The detected hypernym relations should enable us to semantically structure automatically obtained term lists from domain- and user-specific data. We investigated three different hypernymy extraction approaches for Dutch and English: a lexico-syntactic pattern-based approach, a distributional model and a morpho-syntactic method. To test the performance of the different approaches on domain-specific data, we collected and manually annotated English and Dutch data from two technical domains, viz. the dredging and financial domain. The experimental results show that especially the morpho-syntactic approach obtains good results for automatic hypernym extraction from technical and domain-specific texts.
机译:在这项研究中,我们评估了从英语和荷兰语技术文本中自动提取上位词关系的不同方法。所检测到的上位词关系应使我们能够从域和用户特定的数据中语义构造自动获得的术语列表。我们研究了荷兰语和英语的三种不同的高位音提取方法:基于词汇句法模式的方法,分布模型和形态句法方法。为了测试针对特定领域数据的不同方法的性能,我们从两个技术领域(即viz)收集并手动注释了英语和荷兰语数据。疏and和金融领域。实验结果表明,尤其是词法-句法方法在从技术和特定领域的文本中自动提取上位词时取得了良好的效果。

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