Event detection method as machine reading comprehension
In order to improve the performance of event detection task,this article redefines this task as a prompt paradigm.This paradigm uses question-answer pairs to transform event detection into machine reading problems.A pre-training model called WLBert-BiGRU is applied to predict the event triggers in QA pairs.The model uses Weight-Layers strategy to enrich the semantic representation ability of Bert model,and uses Bi-GRU to strengthen the prediction ability of the model to the event triggers.The proposed method is evaluated in ACE2005 data set,the results show that the F1 scores in event trigger recognition and classification have reached 78.1%and 75.1%respectively,which is 4.18%and 4.3%higher than the existing work.
artificial intelligenceevent detectionnatural language processingmachine reading comprehension
万方数据
维普
