论文标题
使用概率决策树微妙地调节微妙的解析区别：名词“补语”条款与相对条款的案例“案例”
Fine-tuning a Subtle Parsing Distinction Using a Probabilistic Decision Tree: the Case of Postnominal "that" in Noun Complement Clauses vs. Relative Clauses
论文作者
论文摘要
在本文中，我们研究了两种不同的方法，以解析英语中的亲戚和名词补充子句，并诉诸于相对的标签，以作为相对代词和互补剂的相应标签。我们使用算法使用通用依赖性来重新标记用口香糖库来重新标记。我们的第二个实验包括使用Treetagger（概率决策树）来学习两种补体和相对用途“ That”的相对用途之间的区别。我们研究了训练集大小对Treetagger精度的影响，以及在审查中的两个结构的牙龈库文件的代表性。我们讨论了这种区别的可学习性的一些语言和结构宗旨。
In this paper we investigated two different methods to parse relative and noun complement clauses in English and resorted to distinct tags for their corresponding that as a relative pronoun and as a complementizer. We used an algorithm to relabel a corpus parsed with the GUM Treebank using Universal Dependency. Our second experiment consisted in using TreeTagger, a Probabilistic Decision Tree, to learn the distinction between the two complement and relative uses of postnominal "that". We investigated the effect of the training set size on TreeTagger accuracy and how representative the GUM Treebank files are for the two structures under scrutiny. We discussed some of the linguistic and structural tenets of the learnability of this distinction.
