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NLP enhancer plugin for Foundry-ES pipeline management system

Prerequisites

For running

  • Java 1.7 JRE

For Development

  • Java 1.7 JDK
  • Maven

Getting the code

cd $HOME
git clone https://github.com/<username>/foundry-nlp-enhancer.git
cd $HOME/foundry-nlp-enhancer

After that expand the UMLS2015 lookup table (which is too big for Github in uncompressed format) locally

gzip -d $HOME/foundry-nlp-enhancer/src/main/resources/edu/uth/clamp/nlp/ner/UMLS2015.txt.gz

Building

First, you need to install local packages in the lib directory to your local Maven repository by running

sh ./install-maven-artifacts.sh

After that run the following to build the Foundry NLP enhancer

sh ./build_jar.sh

Deployment

The enhancer plugin jar and third patry dependencies needs to be copied to the Foundry-ES plugin and lib directories. The Foundry-ES plugin directory is specified in the config.yml file under Foundry-ES/bin directory. E.g.

pluginDir: "/var/data/foundry-es/foundry_plugins/plugins"

The corresponding lib directory for the above plugin directory would be /var/data/foundry-es/foundry_plugins/lib.

Copy the $HOME/foundry-nlp-enhancer/target/NLP_processor_010517-1.0.jar file to the pluginDir specified in the config.yml file.

The following third party libraries needs to be under Foundry-ES plugin lib directory;

bioc-1.0.1.jar
cleartk-eval-2.0.0.jar
cleartk-ml-2.0.0.jar
cleartk-ml-liblinear-2.0.0.jar
cleartk-ml-libsvm-2.0.0.jar
cleartk-ml-opennlp-maxent-2.0.0.jar
cleartk-named-entity-0.6.6.jar
cleartk-token-0.9.0.jar
cleartk-type-system-1.2.0.jar
cleartk-util-0.9.2.jar
commons-io-2.2.jar
context-2012.jar
ctakes-assertion-3.2.1.jar
ctakes-assertion-res-3.2.1.jar
ctakes-chunker-3.2.2.jar
ctakes-chunker-res-3.2.2.jar
ctakes-constituency-parser-3.2.2.jar
ctakes-constituency-parser-res-3.2.2.jar
ctakes-context-tokenizer-3.2.2.jar
ctakes-core-3.2.2.jar
ctakes-core-res-3.2.2.jar
ctakes-dependency-parser-3.2.2.jar
ctakes-dependency-parser-res-3.2.2.jar
ctakes-dictionary-lookup-3.2.2.jar
ctakes-dictionary-lookup-res-3.2.2.jar
ctakes-lvg-3.2.2.jar
ctakes-lvg-res-3.2.2.jar
ctakes-ne-contexts-3.2.2.jar
ctakes-ne-contexts-res-3.2.2.jar
ctakes-pos-tagger-3.2.2.jar
ctakes-pos-tagger-res-3.2.2.jar
ctakes-relation-extractor-3.2.2.jar
ctakes-relation-extractor-res-3.2.2.jar
ctakes-type-system-3.2.0.jar
ctakes-utils-3.2.2.jar
dom4j-1.6.1.jar
ini4j-0.5.2.jar
json-simple-1.1.1.jar
jVinci-2.6.0.jar
jwnl-1.3.3.jar
liblinear-1.94.jar
log4j-api-2.1.jar
log4j-core-2.1.jar
lucene-analyzers-common-4.10.0.jar
lucene-core-4.10.0.jar
lucene-queries-4.10.0.jar
lucene-queryparser-4.10.0.jar
lucene-sandbox-4.10.0.jar
lvg2010dist-0.0.1.jar
nlp-2.4.C.jar
opennlp-maxent-3.0.3.jar
opennlp-tools-1.5.3.jar
ruta-core-2.2.1.jar
ruta-core-ext-2.2.1.jar
ruta-ep-engine-2.2.1.jar
uimafit-1.4.0.jar
uimafit-core-2.1.0.jar
uimaj-adapter-vinci-2.6.0.jar
uimaj-core-2.6.0.jar
uimaj-cpe-2.6.0.jar
uimaj-document-annotation-2.6.0.jar
uimaj-examples-2.4.0.jar
uimaj-tools-2.4.0.jar

Foundry-ES pipeline setup

The NLP enhancer can be configured to be used in the pipeline via the config.yml file. An example configuration is shown below;

pluginDir: "/var/data/foundry-es/foundry_plugins/plugins"
database:
    host: "<mongo-db-host>"
    port: 27017
    db: biocaddie
    collection: records
mq:
    brokerURL: "tcp://localhost:61616?wireFormat.maxInactivityDuration=0"

workflow:
    "BioCaddie Workflow":
        - transform
        - nlp

consumers:
    - uuidGen:
         class: org.neuinfo.foundry.consumers.jms.consumers.plugins.DocIDAssigner
         status: id_assigned
    - transform:
         class: org.neuinfo.foundry.consumers.jms.consumers.plugins.TransformationEnhancer
         status: transformed
         addResourceInfo: false
    - nlp:
         class: edu.uth.biocaddie.ner.BiocaddieNLPEnhancer
         status: nlp_enhanced

Notes

  1. The NER code is in edu.uth.biocaddie.ner package in NLP_NER.java.

  2. To run the program, you need to have NER supporting data and CLAMP resource files in the system.

  3. Change the HomeDir in Config.java to the path where you store the supporting data.

  4. Put the CLAMP resource folder under src/main/resources/.

  5. The function to process the NLP is "NLP_process_json_files" in NLP_NER.java.

  6. Two things can be set in the Config.java.

    1. To disable cache use in MetamapLite, set MetaMapCache=false but it will reduce the process speed. You can also change the maximum cache size for the MetamapLite.
    2. You can decide to use the terminology server in the process or not by setting SynonymsFlag. If SynonymsFlag=true, Config.TerminologyServer should point to the terminology server IP. IF SynonymsFlag=true, four more fields will be added to the results (MeshTerm synonyms, disease synonyms, chemical synonyms, gene synonyms).

  7. An example of input and output are in the "input_example" and "output" folder.

  8. You can use main function in NLP_NER.java to run a test case.