@@ -41,12 +41,37 @@ The following code can be used to create an ontology from an AMR-Lib directory:
For more details on these methods, see the code in **tenet/main.py**.
## 3 - Library Usage for AMR Graphs
## 3 - Library Usage for UNL Graphs
The addition of core methods for supporting UNL graphs is also planned. While waiting for the development of these methods, it is possible to analyze UNL graphs by positioning on an old version (label 0.2.1), or by adapting the existing scripts.
## 4 - Content
## 4 - Quick Execution Example to Test the Library
To quickly test the tenet library named, follow these steps:
3. Create and activate a virtual environment (optional but recommended):
> python3 -m venv tenet_env
> source tenet_env/bin/activate
4. Make sure you have Python 3 installed. Install the required dependencies.
> pip3 install -r requirements.txt
5. Run the test script located at tests/main_tests/test_main_owl_extraction.py. This script contains the tests for the main owl extraction functionality.
6. Review the test results:
- The test results will be displayed in the console output (logs).
- Additionally, the test script may generate output files in the tests/main_tests/test_owl_output directory. Check this directory for any relevant files or logs generated during the test execution.
## 5 - Content
The library groups several packages in the tenet subdirectory. The main methods are defined in the main module (**main.py**). The **extract.py** file has also been developed for command line use (**>> python3 extract.py --source_corpus _input-data_**). The configuration of the library can be adapted by modifying the logging.conf file.
