Visual Editor for creating NLP rules.
Watch a live demo of the NLP editor, and learn more about our future plans in our recent IBM Data Science Community presentation.
Walk through our Tutorial.
Try the editor by following the instructions below.
Clone the repository
git clone git@github.com:CODAIT/nlp-editor.git
Navigate to the source code
cd nlp-editor
The application users a NodeJS server file as proxy, this makes it easy to replace and embed the UI with any other server - Websphere, Nginx, etc.
On a Terminal window, install the Node Version Manager (nvm) as follows:
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.0/install.sh | bash
Reference: https://github.com/nvm-sh/nvm#installing-and-updating
Verify nvm installed properly
> nvm -v
0.39.2
Next, install the required NodeJS version; currently at 18.12.0
nvm install v18.12.0
Verify node and npm installed properly
> node -v
v18.12.0
> npm -v
8.19.2
Install the dependencies
npm install
Build the app
npm run build
Run the app
npm run serve
Open http://localhost:8080 in a web browser.
Additional Prerequsites:
01-ibm_watson_discovery_web_nlp_tool_backend-<date>.tar.gz
supplied to youExtract 01-ibm_watson_discovery_web_nlp_tool_backend-<date>.tar.gz
into a folder of your choice, say watson_nlp_web_tool
Build the container image
cd watson_nlp_web_tool
docker build -t watson_nlp_web_tool:1.0 .
Run the container image with volumes mapped. Note that /path/to/nlp-editor
is the absolute path to the nlp-editor
repository (from Step 1).
docker run -d -v /path/to/nlp-editor/Seer-Core/aql-processor/user-data-in:/app/Seer-Core/aql-processor/user-data-in -v /path/to/nlp-editor/Seer-Core/aql-processor/run-aql-result:/app/Seer-Core/aql-processor/run-aql-result --name watson_nlp_web_tool watson_nlp_web_tool:1.0
Open http://localhost:8080 in a web browser, or use reuse session from Step 1.
Create your NLP model. Use the Tutorial for guidance.
When you are satisfied with your model, click Export. A .zip
file is generated on your local file system.
In Watson Discovery on CloudPak for Data, apply the model by following the steps in Advanced Rules Models.
We welcome your questions, ideas, and feedback. Please create an issue or a discussion thread.
If you are interested in helping make the NLP editor better, we encourage you to take a look at our Contributing page.