Abstract: Disclosed are a Nested Named Entity Recognition method based on part-of-speech awareness, system, device and storage medium therefor. The method uses a BiLSTM model to extract a feature of text word data in order to obtain a text word depth feature, and each text word of text to be recognized is initialized into a corresponding graph node, and a text heterogeneous graph of the text to be recognized is constructed according to a preset part-of-speech path, the text word data of the graph nodes is updated by an attention mechanism, and the features of all graph nodes of the text heterogeneous graph are extracted using the BiLSTM model, and a nested named entity recognition result is obtained after decoding and annotating. The present disclosure can recognize ordinary entities and nested entities accurately and effectively, and enhance the performance and advantages of the nested named entity recognition model.

Abstract: Provided is a pharmaceutical composition and application thereof, specifically, said pharmaceutical composition comprises: salvianolic acid B as a first active ingredient; and ginsenoside Rg1 as a second active ingredient, and the weight ratio of the first active ingredient to the second active ingredient being 5: (1-4.5). The pharmaceutical composition has a better active-ingredient proportion than the prior art, has a better therapeutic efficacy in preventing and/or treating ischemic diseases, and ischemia-reperfusion tissue or organ damage, and can be used for treating ischemia and/or ischemia-reperfusion damage of different tissues and organs.