Constituency Parser
This parser is a wrapper around the opennlp parser version 1.4.  It thus depends on that version of the
opennlp system, but that is a dependency of other ctakes components so you most likely have it already.
Since this module relies on other modules as input (sentence and token segmentation mainly), it contains
configuration files that point at those modules.  These use relative path names for portability, but
do require that the project be extracted at the same level as the other ctakes components. For example, if
your directory structure is:
ctakes/core
ctakes/clinical documents pipeline
ctakes/...

you want it to look like:
ctakes/Constituency Parser

after extracting this module.

Once placed there, the module can be imported to eclipse using File->Import->Existing projects into workspace...


The parser module includes a few different UIMA analysis engines (AEs) for different use cases:
 * AggregateParsingProcessor is mostly for testing/validation.  You can run this in the UIMA Cas Visual Debugger 
 (CVD) by running the cvd launch configuration (in resources/launch/UIMA_CVD--Constituency Parser.launch (right-
 click on file in package explorer->run as...->UIMA_CVD--Constituency Parser.launch)).  Once the CVD window opens,
 load the AE with Run->Load AE..., and navigating to:
  Constituency Parser/desc/analysis_engines/AggregateParsingProcessor.xml
 Load some text either by manually entering it or with File->Open text file..., then Run->Run AE.
 
 * ConstituencyParserAnnotator.xml is a standalone module that is meant to be incorporated into ctakes
 pipelines (for example, upstream from the coreference module).
 
 Both of the above AEs assume some pre-processing as input, namely Sentence and Token segmentation.  They are also
 obviously dependent on the quality of those components for quality output.  With some notes the sentence segmenter
 does not reliably work and the parser will perform poorly (UPMC notes are known to cause trouble).
 
 * ParserEvaluatorAnnotator.xml is used mainly internally for evaluating the parser but may be useful for anyone
 else interested in parser research.  It is used as part of the collection processing engine ParsingCPE.xml, which
 reads a line at a time from a file, where each line contains whitespace-separated tokens of a single sentence.
 
 
 Parser models:
 This release contains two different models.  The default is located in resources/parsermodel, and will be used
 if no configuration settings are changed.  It is trained on a combination of domain-specific and general domain
 text.  Domain specific text includes clinical notes, medpedia articles, cohort queries, clinical questions.  
 General domain text is the Wall Street Journal section of the Penn Treebank.
 
 The second model is in resources/fastmodel.  This model is trained only on the in-domain data.  As a result,
 our preliminary (unpublished) experiments showed it to be a little less accurate and a little faster.