// Define some global attributes include::_globattr.adoc[] Clinical documents pipeline ~~~~~~~~~~~~~~~~~~~~~~~~~~~ This project is the top-level, main project for processing a clinical document through the entire {osp-short} pipeline, including sentence detection, <>, <>, named entity recognition, xref:cd_necontexts[context detection, and negation detection]. The pipeline can process two types of documents - plain text files - Clinical Document Architecture (CDA) XML files that conform to the DTD provided Analysis engines (annotators) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - *AggregateCdaProcessor.xml* for CDA documents conforming to the provided DTD + -- The file +desc/analysis_engine/AggregateCdaProcessor.xml+ is the aggregate analysis engine to use to run the entire pipeline, including the CdaCasInitialzer analysis engine, which reads CDA documents that conform to the DTD provided, and create Segment annotations based on the sections within the CDA document. *Parameters*:: ChunkerCreatorClass;; the full class name of an implementation of the interface edu.mayo.bmi.uima.chunker.ChunkerCreator -- + - *AggregatePlaintextProcessor.xml* for plain text documents + -- The file +desc/analysis_engine/AggregatePlaintextProcessor.xml+ is the aggregate analysis engine to use to run the entire pipeline, including the SimpleSegmentAnnotator analysis engine, which creates a Segment annotation that wraps the entire plain text document. Other annotators in the pipeline require at least one Segment annotation. *Parameters*:: SegmentID;; the identifier or name to assign to the Segment annotation ChunkerCreatorClass;; the full class name of an implementation of the interface edu.mayo.bmi.uima.chunker.ChunkerCreator -- NOTE: The ChunkCreatorClass parameter of both annotators is set to edu.mayo.bmi.uima.chunker.PhraseTypeChunkCreator so that each phrase type gets its own type of annotation, rather than having all chunks be of type Chunk.