This paper presents a corpus and experiments to mine possession relations from text. Specifically, we target alienable and control possessions and assign temporal anchors indicating when a possession relation holds between the possessor and possessee. We work with intra-sentential possessor and possessees that satisfy lexical and syntactic constraints. We experiment with traditional classifiers and neural networks to automate the task. In addition, we analyze the factors that help to determine possession existence and possession type and common errors made by the best performing classifiers. Experimental results show that determining possession existence relies on the entire sentence, whereas determining possession type primarily relies on the verb, possessor and possessee.

本文提出了从文本中挖掘占有关系的语料库和实验。具体来说，我们以可转让和控制财产为目标，并分配时间锚点，指示占有者和被占有者之间的占有关系何时成立。我们与满足词汇和句法约束的句内占有者和占有者一起工作。我们尝试使用传统的分类器和神经网络来自动化任务。此外，我们分析了有助于确定控球存在和控球类型的因素以及表现最好的分类器所犯的常见错误。实验结果表明，占有存在的判断依赖于整个句子，而占有类型的判断主要依赖于动词、占有者和占有者。