以下面的句子作为例子（来自GATE官方教程幻灯片：模块11 https://gate.ac.uk/sale/talks/gate-course-may10/track-3/module-11-ml-adv/）：
I was told the item was in stock and next day delivery. After a couple of days i chased them to be told there was an error, none in stock. Chased again after a few days, still no stock then found out that they had billed me right from the beginning. So they have had my money for over a week - have no idea when they will have stock- and i have done all the chasing. Despite what others say in eight years of Internet shopping worst experinece to date bar none.
当整个句子被标记为anntation并被视为GATE机器学习PR（批量学习）中的实例时，GATE将如何处理学习过程？
我有两个猜测 . 一个是GATE使用人类语言自动标记句子中的每个单词并收集这些功能以构建分类模型 . 另一个是GATE简单地将句子转换为数学变量，如矢量，并根据语言学特征训练模型，例如使用了多少名词，adj，adv .
我不确定哪一个是正确的，或者是否会对该过程有另一种解释 . 希望有人可以给出确认或任何相关信息 .
谢谢！
1 回答
GATE根据配置xml文件中的定义构建模型 . 除了实例类型，可能会有注释，如Token（具有功能root，POS，..）或N-gram或您自己的JAPE规则创建的注释（带功能） . Gate将使用这些定义并构建模型 .