A device may receive training data that includes datasets associated with natural language processing, and may mask the training data to generate masked training data. The device may train a masked event C-BERT model, with the masked training data, to generate pretrained weights and a trained masked event C-BERT model, and may train an event aware C-BERT model, with the training data and the pretrained weights, to generate a trained event aware C-BERT model. The device may receive natural language text data identifying natural language events, and may process the natural language text data, with the trained masked event C-BERT model, to determine weights. The device may process the natural language text data and the weights, with the trained event aware C-BERT model, to predict causality relationships between the natural language events, and may perform actions, based on the causality relationships.
UTILIZING MACHINE LEARNING MODELS AND IN-DOMAIN AND OUT-OF-DOMAIN DATA DISTRIBUTION TO PREDICT A CAUSALITY RELATIONSHIP BETWEEN EVENTS EXPRESSED IN NATURAL LANGUAGE TEXT