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Abstract In order to solve the problem of false information and duplication in the summarizations generated by the T5
PEGASUS model, a text summarization model based on T5 PEGASUS and DeepKE - T5 PEGASUS-DK is proposed.
This model combines the T5 PEGASUS model with DeepKE framework. Firstly, the Pkuseg segmentation method is used
to improve the segmentation performance. Then, the DeepKE framework is used to extract triads from text. Finally, the
word vector set of triads is concatenated with the representation vector of text. By establishing a mapping relationship
between text and triads, the model can extract factual knowledge and extract information that is more consistent with the
original content as a summary. The experimental results show that the T5 PEGASUS-DK model has the highest ROUGE
value, and the generated abstracts are more authentic, coherent, and consistent with the original content.
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