• Clone repository or download files
  • Enter the directory
  • Run: pip install -e .


  • framenet_tools download acquires all required data and extracts it , optionally --path can be used to specify a custom path; default is the current directory. NOTE: After extraction the space occupied amounts up to around 9GB!
  • framenet_tools convert can now be used to generate the CoNLL datasets This function is analogous to pyfn and simply propagates the call.
  • framenet_tools train trains a new model on the training files and saves it, optionally --use_eval_files can be specified to train on the evaluation files as well. NOTE: Training can take a few minutes, depending on the hardware.

For further information run framenet_tools --help


Alternatively provides a also the ability to convert FN data to CoNLL using pyfn. In this case, manually download and extract the FrameNet dataset and adjust the path inside the script.