How can I train NLTK on the entire Penn Treebank corpus?
我怎样才能培养NLTK整个宾州树库语料？
Again, parsers for probabilistic parsing are also bundled with NLTK.
同样，用于概率解析的解析器也捆绑到了NLTK中。
A few special keys are used in NLTK, different ones by the various subpackages.
在NLTK中使用了一些专门的键，不同的键由不同的子程序包所使用。
NLTK includes an excellent algorithm for word stemming, and lets you customize stemming algorithms further to your liking.
NLTK中包括一个用于单词词干提取的极好算法，并且让您可以按您的喜好定制词干提取算法。
Of course, you can equally analyze frequencies of higher-level grammatical features, or even of data sets unrelated to NLTK.
当然，您也可以这样分析高层次语法特性或者甚至是与NLTK无关的数据集的频率分布。
NLTK corpora documents often come pre-tagged for parts of speech, but you can certainly add your own tags to untagged documents.
NLTK 全集文档通常有部分专门语言已经预先添加了标签，不过，您当然可以 将您自己的标签添加到没有加标签的文档。
Of particular use to the new user of NLTK -- including the author, as he wrote this article -- are the series of nine tutorials on NTLK.
对NLTK的新用户来说 ——包括作者，虽然他撰写了本文 ——seriesofninetutorialson NTLK 是非常有使用价值的。
For example, NLTK has a whole framework for text classification using statistical techniques like "naive Bayesian" and "maximum entropy" models.
例如，NLTK有一个完整的框架，用于通过类似于“naiveBayesian”和“maximumentropy”等模型的统计技术进行文本分类。
Much of what you can do with NLTK, particularly at its lower levels, is not that much different from what you can do with Python's basic data structures.
您可以使用NLTK完成的很多工作，尤其是低层的工作，与使用Python的基本数据结构来完成相比，并没有太大的区别。
I didn't know how to handle those problems until I found the NLTK(nature language tools kit). I used the NLTK to lemmatize those words to a normal form.
为了使他们能够还原成单词的原始形态，我使用了NLTK（naturelanguagetoolskit）来做词形还原。
Even beyond top-down and shift-reduce parser, NLTK also offers "chart parsers" that create partial hypotheses that a given sequence can be continued to fulfill a rule.
甚至，除了top - down和shift - reduce解析器以外，NLTK还提供了“chart解析器”，它可以创建部分假定，这样一个给定的序列就可以继而完成一个规则。
While NLTK comes with a number of corpora that have been pre-processed (often manually) to various degrees, conceptually each layer relies on the processing in the adjacent lower layer.
尽管NLTK 附带了很多已经预处理（通常是手工地）到不同程度的全集，但是概念上每一层 都是依赖于相邻的更低层次的处理。
While NLTK comes with a number of corpora that have been pre-processed (often manually) to various degrees, conceptually each layer relies on the processing in the adjacent lower layer.
尽管NLTK附带了很多已经预处理(通常是手工地)到不同程度的全集，但是概念上每一层都是依赖于相邻的更低层次的处理。
Forgive me if I stumble through my explanations of the quite remarkable Natural Language Toolkit (NLTK), a wonderful tool for teaching, and working in, computational linguistics using Python.
如果在对意义非凡的自然语言工具包(NLTK)的说明中出现了错误，请您谅解。NLTK是使用Python教学以及实践计算语言学的极好工具。
Forgive me if I stumble through my explanations of the quite remarkable Natural Language Toolkit (NLTK), a wonderful tool for teaching, and working in, computational linguistics using Python.
如果在对意义非凡的自然语言工具包(NLTK)的说明中出现了错误，请您谅解。NLTK是使用Python教学以及实践计算语言学的极好工具。
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