Patent ID: 11893345
Assignee: ADOBE INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 16:
17. A method for training a neural network, comprising:
receiving training data including documents comprising a plurality of words organized into a plurality of sentences, the words comprising an event trigger word and argument words, and the training data further including ground truth relationships between the event trigger word and the argument words;
generating word representation vectors for the words;
generating a plurality of document structures including a semantic structure based on the word representation vectors, a syntax structure representing dependency relationships between the words, and a discourse structure representing discourse information based on the plurality of sentences;
generating relationship representation vectors based on the document structures;
predicting relationships between the event trigger word and the argument words based on the relationship representation vectors;
computing a loss function by comparing the predicted relationships to the ground truth relationships; and
updating parameters of a neural network based on the loss function.