We will use the OpenNLP and Stanford APIs to demonstrate parsing and the extraction of relation information. LingPipe can also be used but will not be discussed here. An example of how LingPipe is used to parse biomedical literature can be found at http://alias-i.com/lingpipe-3.9.3/demos/tutorial/medline/.
Parsing text is simple using the ParserTool class. Its static parseLine method accepts three arguments and returns a Parser instance. These arguments are:
A string containing the text to be parsed
A
ParserinstanceAn integer specifying how many parses are to be returned
The Parser instance holds the elements of the parse. The parses are returned in order of their probability. To create a Parser instance, we will use the ParserFactory class' create method. This method uses a ParserModel instance that we will create using the en-parser-chunking.bin file.
This process is shown here, where an input stream for the model file is created using a try-with-resources block...