Named entity recognition method based on rules and improved pre-training model

The invention discloses a named entity recognition method based on rules and an improved pre-training model. According to the method, on the basis of BERT pre-training, field data which are the same as downstream tasks are added to continue pre-training, and then fine adjustment is carried out on named entity recognition tasks; meanwhile, considering that part-of-speech can express attribute information of important words, additional feature information is added in the internal structure of the BERT model to enhance the recognition performance of the system; in the aspect of deep learning model construction, a convolutional neural network and a bidirectional recurrent neural network are integrated to carry out sentence-level feature extraction on a text, finally, an entity result recognized by the model is corrected in combination with rules, whether the entity length is smaller than a certain value or not is judged, and if the front is adjectives, a new entity is spliced to serve as the final entity word; ac