smile_ks_parsetokenize

SMILE Knowledge Source: ParseTokenize

Setup

1 GraphDB Installation

• GraphDB can be installed for your distribution.
• Make sure it's running port 7200, e.g. http://localhost:7200.
• Make sure you have GraphDB running on http://localhost:7200.

2 GraphDB Repository Creation

• For testing, make sure the username and password are set to admin
• Create a new test repository. Go to http://localhost:7200
  • Create new repository:
    • Name the repository (Repository ID) as smile
    • Set context index to True *(checked).
    • Set query timeout to 45 second.
    • Set the Throw exception on query timeout checkmark to True (checked)
    • Click on create repository.
  • Make sure the repository rin in "Running" state.
• See instruction below for troubleshooting

3 GraphDB Configuration

A few notes on configurting SMILE to connect to the database.

• The main SMILE Flask application can be configured in the config/local_config.yml file.
• Knowledge source that are running in a Docker instance must use the "Docker" version of the config file: config/local_config_test.yml.

4 Install Prolog

Install swi-prolog for your environment.

5. Install StanfordCoreNLP packages

• cd src/smile_ks_parsetokenize/libs/corenlp/
• chmod +x nlp_server.sh
• curl https://downloads.cs.stanford.edu/nlp/software/stanford-corenlp-4.3.1.zip > stanford-corenlp-4.3.1.zip
• open stanford-corenlp-4.3.1.zip
• curl https://downloads.cs.stanford.edu/nlp/software/stanford-parser-4.2.0.zip > stanford-parser-4.2.0.zip
• open stanford-parser-4.2.0.zip
• cd ../../../..

4 Setup smile-ks-qa1

cd src/smile_ks_parsetokenize conda env create -f PyParseTokenize.yml ./scripts/setup_folders.sh

To run example

You will need two terminals.

Term 1, run: cd src/smile_ks_parsetokenize/libs/ ./corenlp/nlp_server.sh This will start a NLP server at http://localhost:9000. It will run in the background.

Term 2: Run ParseTokenize example conda activate PyParseTokenize cd src python -m smile_ks_parsetokenize.main

To run KnowledgeSource Listener

conda activate PyParseTokenize cd src python -m smile_ks_parsetokenize.listener