2022
DOI: 10.3390/electronics11142161
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RECA: Relation Extraction Based on Cross-Attention Neural Network

Abstract: Extracting entities and relations, as a crucial part of many tasks in natural language processing, transforms the unstructured text information into structured information and provides corresponding data support for knowledge graph (KG) and knowledge vault (KV) construction. Nevertheless, the mainstream relation-extraction methods, the pipeline method and the joint method, ignore the dependency between the subject entity and the object entity. This work introduces a pre-trained BERT model and a dilated gated c… Show more

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“…features sequentially, then performs pooling down sampling to eliminate noise and instability, and finally feeds the processed data into an LSTM network[6].…”
mentioning
confidence: 99%
“…features sequentially, then performs pooling down sampling to eliminate noise and instability, and finally feeds the processed data into an LSTM network[6].…”
mentioning
confidence: 99%