ENCODER, SYSTEM AND METHOD FOR METAPHOR DETECTION IN NATURAL LANGUAGE PROCESSING

Provided is an encoder, system and method for metaphor detection in natural language processing. The system comprises an encoding module configured to convert words included in a sentence into BiLSTM representation vectors; a first encoder configured to generate a first entire representation vector of a WSD resolving task; a second encoder configured to generate a second entire representation vector of an MD task; and a multi-task learning module configured to perform knowledge transfer between the first and second encoders. Wherein, each of the first and second encoders includes a graph convolutional neural network (GCN) module configured to encode a link between a target word and a core word to generate GCN representation vectors; a control module configured to regulate the GCN representation vectors to generate an entire representation vector.