A machine reading comprehension method and apparatus based on BERT, and a computer device and a computer-readable storage medium, which relate to the technical field of artificial intelligence and the technical field of neural networks. The method comprises: training a first pre-set pre-training language model according to a question-document pair to be trained, so as to generate a document sorting model (S102); training a pre-set multi-document answer prediction model according to the question-document pair to be trained, so as to generate a reading comprehension model (S103); on the basis of the document sorting model and according to a question-document pair to be predicted, outputting a target document corresponding to a second question (S105); and on the basis of the reading comprehension model and according to the second question and the target document, acquiring target text in the target document that is output by the reading comprehension model, and taking the target text as a reading comprehension answer to the second question (S106). A multi-document reading comprehension question is converted into a single-document reading comprehension question, so as to reduce the interference of answer extraction during reading comprehension, thereby improving the accuracy of a multi-document reading comprehension answer.
MACHINE READING COMPREHENSION METHOD AND APPARATUS BASED ON BERT, AND DEVICE AND STORAGE MEDIUM