This is a very easy-to-use and simple example(terminal based) of the weaviate Named Entity Recognition module.
In this example, we have some sentences (can be from any source, like all introductory sentences from a slack channel) and we extract entities like person name, location, organization from those and collect the data in a file. This can be used to collect useful data from conversations, emails, messages etc.
To run the example, make sure to have docker and docker-compose and start/spin-up the weaviate instance using the command:
"docker-compose up -d" (Run this in same directory as the project)
Now, run the data.py file using "python ./data.py" to load the data in weaviate.
Then run the command "python ./test.py" to test if all works well. (Optional)
Then run the command "python ./add.py" to add the data (the extracted entities) to the csv file.
Below is the result of the test.py file:
