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。
The documentation for NLTK is accessible through the project home page.
NLTK的文档可以自项目主页获得。
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 has other important features that this brief introduction could not get to.
NLTK还有其他本篇简短介绍中不能涵盖的重要功能。
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。
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。
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。
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