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Information Extraction for Policy Analysis

This project uses the Odin extraction framework to extract information relevant to policy analysis from text.

What you'll need...

  1. anaconda for Python 2.7
  2. Java 8
  3. sbt

Process

To run the shell for grammar testing, run ./shell from the command line. To run the extractor over many documents, follow the steps below.

Convert PDFs into txt documents

The main extraction system assumes text format. If you have (searchable) PDF format, you can use the script at src/main/python/textFromDir.py to do the conversion. The script uses python libraries (crucially, pdfminer) that require installation. You can install via conda using

conda env create -f src/main/python/environment.yml

then activate the environment using

source activate collab

To actually run the converter, use something like

python ./src/main/python/textFromDir.py /path/to/pdf /path/to/raw

This system doesn't work well on tables yet.

Clean up txt documents

Text from PDFs typically has mid-sentence line breaks that confuse the NLP preprocessors. To prepare the raw text for extraction, adjust src/main/resources/reference.conf to match your file locations. Specifically, you need to adjust collab.data. Then, run

sbt "runMain com.github.danebell.collab.korrect.KorrectDocuments"

Run the extraction system

Adjust collab.out to be the directory where you want the relation extractions printed. Then, run

sbt "runMain com.github.danebell.collab.ReadPapers"

This is best done on a computer with many threads and lots of memory. To make use of this memory, adjust ./.sbtopts to an appropriate value, e.g. -J-Xmx63G for 63 GB of memory.

If you re-run the system (for example, after making rule changes), the previous results will not be overwritten. This is to allow for easy restarting after crashes or other interruptions. If you want to overwrite old results, you must delete them first.

Join the output

There's a script to join the output into a single document. Ensure that the collab.data location is set correctly, then run

sbt "runMain com.github.danebell.collab.utils.MergeOutput"

For very large collections, it will be faster to use command-line functions, so a script is provided at ./merge.sh. Note that you must run this script from the collab.data location.

Citing

If you use this repository, please cite the following work:

Bell, Emily V., Elizabeth A. Albright, and Dane Bell. “Mitigating Hazard through Collaborative PolicyNetworks: A Study of Policy Learning in Urban Stormwater Management.” Association for PublicPolicy Analysis and Management Fall Research Conference, Denver, CO, November 2019.