Papers › Enriching Pre-trained Language Model with Entity Information for Relation Classification

Enriching Pre-trained Language Model with Entity Information for Relation Classification

20 May 2019arXiv:1905.08284archive 2025-07-28

Shanchan Wu, Yifan He

Relation classification is an important NLP task to extract relations between entities. The state-of-the-art methods for relation classification are primarily based on Convolutional or Recurrent Neural Networks. Recently, the pre-trained BERT model achieves very successful results in many NLP classification / sequence labeling tasks. Relation classification differs from those tasks in that it relies on information of both the sentence and the two target entities. In this paper, we propose a model that both leverages the pre-trained BERT language model and incorporates information from the target entities to tackle the relation classification task. We locate the target entities and transfer the information through the pre-trained architecture and incorporate the corresponding encoding of the two entities. We achieve significant improvement over the state-of-the-art method on the SemEval-2010 task 8 relational dataset.

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Valdegg/anlp_rbert mentioned on GitHub report
chielingyueh/anaphora_resolution_chemical_patents mentioned on GitHubpytorchApache-2.0 report
mickeystroller/R-BERT mentioned on GitHubpytorchGPL-3.0 report
monologg/R-BERT mentioned on GitHubpytorch report
wang-h/bert-relation-classification mentioned on GitHubpytorch report

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get_args monologg/R-BERT/predict.py community (archive-listed) ran · our draft was wrong Apache-2.0 (permissive) · 107869d936646d01 · report
get_device monologg/R-BERT/predict.py community (archive-listed) ran · our draft was wrong Apache-2.0 (permissive) · 88395eef09dea094 · report
semeval_scorer onehaitao/R-BERT-relation-extraction/evaluate.py community (archive-listed) ran · our draft was wrong fingerprinted MIT (permissive) · b31fd07675860198 · report
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Tasks

General ClassificationLanguage ModelingLanguage ModellingRelation ClassificationRelation ExtractionSentence

1 archive task tag without a task page not shown.

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Relation Extraction SemEval-2010 Task-8 R-BERT F1 89.25 #15 of 31 Archive leaderboard report
Relation Extraction TACRED R-BERT F1 69.4 #25 of 40 Archive leaderboard report

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Methods

AdamAttentionAttention DropoutBERTDense ConnectionsDropoutLayer NormalizationLinear LayerLinear Warmup With Linear DecayMulti-Head AttentionResidual ConnectionSoftmaxWeight DecayWordPiece

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