Patent ID: 11893352
Assignee: ADOBE INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 15:
16. A method of training a neural network, the method comprising:
receiving a training phrase including a subject entity, an object entity, a candidate word, one or more additional words, and a ground truth relationship between the subject entity and the object entity;
generating a path vector representing a transformation between the subject entity and the object entity using a path network, wherein the path vector is generated based on a word representation for the subject entity and the object entity, respectively;
computing an exclusion vector corresponding to the candidate word, wherein the exclusion vector is based on the one or more additional words from the training phrase excluding the candidate word, the subject entity, and the object entity;
computing a transfer vector corresponding to the candidate word based on the path vector and the exclusion vector;
including the candidate word in a dependency path between the subject entity and the object entity based on a similarity between the transfer vector and the word representation for the candidate word;
generating a path representation based on the dependency path;
predicting a relationship between the subject entity and the object entity based on the path representation using a decoder;
comparing the ground truth relationship with the predicted relationship to produce a prediction loss; and
training the path network based on the prediction loss.