CPC G06F 40/284 (2020.01) [G06F 40/126 (2020.01); G06F 40/211 (2020.01); G06F 40/30 (2020.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01)] | 20 Claims |
1. A method for natural language processing, comprising:
receiving a query about an event;
receiving a document comprising a plurality of words organized into a plurality of sentences, the words comprising an event trigger word corresponding to the event and an argument candidate word;
generating word representation vectors for the words by generating a first word representation vector for the event trigger word;
generating a second word representation vector for the argument candidate word;
generating a plurality of document structures including a semantic structure for the document based on the first word representation vector and the second word representation vector, a syntax structure based on a sentence-level dependency relationship, and a discourse structure representing document-level discourse information based on the plurality of sentences;
generating a relationship representation vector based on the plurality of document structures;
predicting, using a graph-based neural network, a relationship between the event trigger word and the argument candidate word based on the relationship representation vector; and
generating an answer to the query based on the predicted relationship between the event trigger word and the argument candidate word.
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