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Specifically, we design a domain semantics-enhanced transformer mechanism that automatically enhances the railway semantics from a dedicated railway lexicon. We further introduce piece-wise convolution neural networks to explore the fine-grained features contained in the structure of triple knowledge. With the domain semantics and fine-grained features, our model can fully understand the domain text and thus improve the performance of relation classification. 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