The question is very open ended. That said, rather than choose one, below is a comparison depending on the language that you would like to use (since there are good libraries available in both languages).
Python
In terms of Python, the first place you should look at is the Python Natural Language Toolkit. As they note in their description, NLTK is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning.
There is also some excellent code that you can look up that originated out of Google's Natural Language Toolkit project that is Python based. You can find a link to that code here on GitHub.
Java
The first place to look would be Stanford's Natural Language Processing Group. All of software that is distributed there is written in Java. All recent distributions require Oracle Java 6+ or OpenJDK 7+. Distribution packages include components for command-line invocation, jar files, a Java API, and source code.
Another great option that you see in a lot of machine learning environments here (general option), is Weka. Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.