clemessien / date-annotator Goto Github PK
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License: Apache License 2.0
Tried several modes for annotation of id and location subentities. The closest I came across was the ner_deid_subentity_augmented model. While it detects
states and countries, it does a poor job for id annotation.
For a sample text
alternate no is 5731111111. Tom's email is [email protected]. My favorite website is
http://www.goal.com. My social security is 886-12-1234 or simpley written as 886121234. I was born on 1st of January 1900.
Today is 07/09/2021. I saw the doctor at Boone Medical Center.
A. Record date : 2093-01-13, David Hale, M.D., Name : Hendrickson, Ora MR. # 7194334
Date : 01/13/93 PCP : Oliveira, 25-year-old, Record date : 1-11-2000. Cocke County Baptist Hospital. 0295 Keats Street.
Phone +1 (302) 786-5227. Patient's complaints first surfaced when he started working for Brothers Coal-Mine.
The output is:
Entity | begin | end | label | confidence |
---|---|---|---|---|
Wolfgang | 11 | 18 | PATIENT | 0.9881 |
Columbia | 34 | 41 | COUNTRY | 0.9804 |
Missouri | 43 | 50 | STATE | 0.6373 |
886037234 | 192 | 200 | MEDICAL RECORD | 0.8157 |
1st of January 1900 | 217 | 235 | DATE | 0.64545 |
07/09/2021 | 247 | 256 | DATE | 1.0 |
If ssh is already installed and enabled, skip this step or else run the following commands;
run conda install -c johnsnowlabs spark-nlp
Register for spark nlp jsl license at https://nlp.johnsnowlabs.com/docs/en/licensed_install
Run the following command: pip install -q spark-nlp-jsl==${version} --extra-index-url https://pypi.johnsnowlabs.com/${secret.code} --upgrade
run spark-shell --packages com.johnsnowlabs.nlp:spark-nlp_2.12:3.1.0 to Load Spark NLP with pyspark
Run the test script i.e. spark_nlp_test.py located in server folder
A possible solution I tried was to download the ML mode specifically the "clinical ner" model which can handle the date annotation and de-identification and I am facing a major blocker as it appears that this model and similar models are not accessible. The error message is Permission Denied
So I would try to look into the source code to see if there is a link to where the models that successfully download during runtime are located and attempt to download them for use offline
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