Papers › Multi²OIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERT

Multi²OIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERT

17 Sep 2020arXiv:2009.08128archive 2025-07-28

Youngbin Ro, Yukyung Lee, Pilsung Kang

In this paper, we propose Multi²OIE, which performs open information extraction (open IE) by combining BERT with multi-head attention. Our model is a sequence-labeling system with an efficient and effective argument extraction method. We use a query, key, and value setting inspired by the Multimodal Transformer to replace the previously used bidirectional long short-term memory architecture with multi-head attention. Multi²OIE outperforms existing sequence-labeling systems with high computational efficiency on two benchmark evaluation datasets, Re-OIE2016 and CaRB. Additionally, we apply the proposed method to multilingual open IE using multilingual BERT. Experimental results on new benchmark datasets introduced for two languages (Spanish and Portuguese) demonstrate that our model outperforms other multilingual systems without training data for the target languages.

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Code

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3ran · our draft was wrong
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ArgExtractorLayer youngbin-ro/Multi2OIE/model.py official repository ran MIT (permissive) · 19d102227a9593b8 · report
ArgModule youngbin-ro/Multi2OIE/model.py official repository ran fingerprinted MIT (permissive) · a33040d181118428 · report
_get_activation_fn youngbin-ro/Multi2OIE/model.py official repository ran · our draft was wrong MIT (permissive) · cc650062db9ad0fd · report
_get_clones youngbin-ro/Multi2OIE/model.py official repository ran · our draft was wrong MIT (permissive) · cb0b5b4e93484793 · report
_get_position_idxs youngbin-ro/Multi2OIE/model.py official repository ran · our draft was wrong fingerprinted MIT (permissive) · 201ed56d9f42b81e · report
_get_pred_feature youngbin-ro/Multi2OIE/model.py official repository ran · fixture could not drive it fingerprinted MIT (permissive) · 2a90b356afe75518 · report
Multi2OIE youngbin-ro/Multi2OIE/model.py official repository unverified MIT (permissive) · 07fdc99b724a3587 · report

Tasks

Computational EfficiencyOpen Information Extraction

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Open Information Extraction CaRB Multi2OIE F1 52.3 #7 of 29 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

Absolute Position EncodingsAdamAttentionAttention DropoutBERTBPEDense ConnectionsDropoutLabel SmoothingLayer NormalizationLinear LayerLinear Warmup With Linear DecayMulti-Head AttentionPosition-Wise Feed-Forward LayerResidual ConnectionSoftmaxTransformerWeight DecayWordPiece

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