FAMIE is a comprehensive and efficient active learning (AL) toolkit for multilingual information extraction (IE). FAMIE is designed to address a fundamental problem in existing AL frameworks where annotators need to wait for a long time between annotation batches due to the time-consuming nature of model training and data selection at each AL iteration. With a novel proxy AL mechanism and the integration of our SOTA multilingual toolkit Trankit, FAMIE can quickly provide users with a labeled dataset and a ready-to-use model for different IE tasks over 100 languages.
FAMIE’s github: https://github.com/nlp-uoregon/famie
FAMIE’s demo website: http://nlp.uoregon.edu:9000/