Papers with multiple-step pipelines

1 papers
REBEL: Relation Extraction By End-to-end Language generation (2021.findings-emnlp)

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Challenge: Existing approaches to extract relation triplets from text often involve multiple-step pipelines that propagate errors or are limited to a small number of relation types.
Approach: They propose to use autoregressive seq2seq models to simplify Relation Extraction by expressing triplets as a sequence of text and a model that performs end-to-end relation extraction for more than 200 different relation types.
Outcome: The proposed model achieves state-of-the-art on an array of Relation Extraction and Relation Classification benchmarks and achieves top performance in most of them.

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