Extraction method for test question corpus emotion and reason sentence pair

The invention discloses a method for extracting sentences of emotions and reasons in a test question text based on a graph convolutional network, and the method comprises the following steps: obtaining test question text data, and carrying out the sentence segmentation preprocessing of the data; converting the sentences into vector representation by using a BERT pre-training language model; using a full connection layer network to generate corresponding pairing combination representations from the sentence representations; embedding a vector by using a relative position to enhance a pairing combination representation vector; performing average pooling on the sentence vector representation to obtain document representation; carrying out coding interaction on four expressions of an emotion sentence, a reason sentence, a pairing combination and a document by using a graph convolutional network; and finally, predicting whether a pairing combination is established by using a multi-layer perceptron model. According