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CLEVER (CL-inical EVE-nt R-ecognizer)

This repo includes the Python3 version of CLEVER code from the Program Evaluation Resource Center, Office of Mental Health and Suicide Prevention, Department of Veterans Affairs.

Original Development Team Suzanne Tamang Manual Tanya

Continued Developiment Team Suzanne Tamang Asqar Shotqara Esther Meerwijk

Create an output folder. Run the shell scripts in each of the step folders under ./src. The scripts are provided as examples. Change the target concept and output folder as needed. Make sure that scripts retain their Unix file format. DOS line endings cause trouble. Make sure that the scripts do not end with an empty line.

Step 1 is not currently used.

Step 2 tags text from the corpus for terms from the dictionary. It returns the tagged terms and some of its context, referred to as snippets, in extraction files, one for each worker.

Step 3 combines the extraction files with meta-data and returns one file: linkedAnts.txt.

Step 4 labels the snippets in the linkedAnts file as positive, negative if a negation term is found, or not applicable if snippets do not apply to the experiencer (e.g. family members). It returns three files: allPos_unfiltered.txt, allNeg_unfiltered.txt, and allNA_unfiltered.txt. In older versions of CLEVER without step 5 the three files were named allPos.txt, allNeg.txt and allNA.txt.

Step 5 filters out snippets with assessments from the snippets that were labelled positive or negative and returns two files: allPos.txt and allNeg.txt. This step also contains a script to drop snippets that are cross-tagged. Meaning, they are tagged for multiple targets that are related but should only be tagged for one of those targets. This script is not required for step 5 to run successfully and may not apply to your use of CLEVER.

clever-py3