Accenture Global Solutions Limited

Mayuresh Anand

Shubhashis Sengupta

Andrew E Fano

Roshni Ramesh Ramnani

Vivek Kumar Khetan

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

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Santa Barbara, CA, United States of America

Mayuresh Anand