We will use OpenNLP's SentenceDetectorME class to illustrate the training process. This class has a static train method that uses sample sentences found in a file. The method returns a model that is usually serialized to a file for later use.
Models use special annotated data to clearly specify where a sentence ends. Frequently, a large file is used to provide a good sample for training purposes. Part of the file is used for training purposes, and the rest is used to verify the model after it has been trained.
The training file used by OpenNLP consists of one sentence per line. Usually, at least 10 to 20 sample sentences are needed to avoid processing errors. To demonstrate this process, we will use a file called sentence.train. It consists of Chapter 5, Twenty Thousand Leagues Under the Sea, by Jules Verne. The text of the book can be found...
