scrubadub-stanford 2.1.1

Use the Stanford NER model to clean personally identifiable information from dirty dirty text.

scrubadub removes personally identifiable information from text. scrubadub_stanford is an extension that uses Stanford’s NER model to remove personal information from text.

This package contains three flavours of interfacing with Stanford’s NER models that can be used as a detector:

• scrubadub_stanford.detectors.StanfordEntityDetector - A detector that uses the Stanford NER model to find locations, names and organizations. Download size circa 250MB.

• scrubadub_stanford.detectors.CoreNlpEntityDetector - The same interface as the StanfordEntityDetector, but using Stanza’s CoreNLPClient to interface with the CoreNLP Java Server. Download size circa 510MB.

• scrubadub_stanford.detectors.StanzaEntityDetector - Similar to the above but using Stanza’s native Python pipelines. Download size circa 210MB. No Java required. This is the recommended detector for speed and footprint.

Prerequisites

A minimum version of Java Runtime Environment 8 is required for StanfordEntityDetector and CoreNlpEntityDetector. Check which version by running:

$ java -version

It should be at least version 1.8, but if not, please run the following commands:

Linux:

$ sudo apt update
$ sudo apt install openjdk-8-jre

MacOS:

$ brew tap adoptopenjdk/openjdk
$ brew install adoptopenjdk8-jre

For more information on how to use this package see the scrubadub stanford documentation and the scrubadub repository.

New maintainers

LeapBeyond are excited to be supporting scrubadub with ongoing maintenance and development. Thanks to all of the contributors who made this package a success, but especially @deanmalmgren, IDEO and Datascope.