Papers › Text2NKG: Fine-Grained N-ary Relation Extraction for N-ary relational Knowledge Graph...

Text2NKG: Fine-Grained N-ary Relation Extraction for N-ary relational Knowledge Graph Construction

8 Oct 2023arXiv:2310.05185archive 2025-07-28

Haoran Luo, Haihong E, Yuhao Yang, Tianyu Yao, Yikai Guo, Zichen Tang, Wentai Zhang, Kaiyang Wan, Shiyao Peng, Meina Song, Wei Lin, Yifan Zhu, Luu Anh Tuan

Beyond traditional binary relational facts, n-ary relational knowledge graphs (NKGs) are comprised of n-ary relational facts containing more than two entities, which are closer to real-world facts with broader applications. However, the construction of NKGs remains at a coarse-grained level, which is always in a single schema, ignoring the order and variable arity of entities. To address these restrictions, we propose Text2NKG, a novel fine-grained n-ary relation extraction framework for n-ary relational knowledge graph construction. We introduce a span-tuple classification approach with hetero-ordered merging and output merging to accomplish fine-grained n-ary relation extraction in different arity. Furthermore, Text2NKG supports four typical NKG schemas: hyper-relational schema, event-based schema, role-based schema, and hypergraph-based schema, with high flexibility and practicality. The experimental results demonstrate that Text2NKG achieves state-of-the-art performance in F1 scores on the fine-grained n-ary relation extraction benchmark. Our code and datasets are publicly available.

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Code

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1ran · our draft was wrong
1ran · fixture could not drive it
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BioEncoder lhrlab/text2nkg/hyperred_data_process.py official repository ran MIT (permissive) · b15e1145195f287e · report
Entity lhrlab/text2nkg/hyperred_data_process.py official repository ran · metamorphic tier: deterministic MIT (permissive) · 4161204c355ff4f5 · report
add_tag_joint_label lhrlab/text2nkg/hyperred_data_process.py official repository ran MIT (permissive) · e82ac45ea887bc39 · report
add_tokens lhrlab/text2nkg/hyperred_data_process.py official repository ran MIT (permissive) · 51d44540fb9cd150 · report
convert_sent_to_tags lhrlab/text2nkg/hyperred_data_process.py official repository ran MIT (permissive) · ace46dde5211f557 · report
sset LHRLAB/Text2NKG/run_re.py official repository ran · fixture could not drive it fingerprinted MIT (permissive) · 03619aadbbc021c8 · report
Relation lhrlab/text2nkg/hyperred_data_process.py official repository unverified MIT (permissive) · 09904326420aaef1 · report
Sentence lhrlab/text2nkg/hyperred_data_process.py official repository unverified MIT (permissive) · 81db230e87f76be0 · report
SparseCube lhrlab/text2nkg/hyperred_data_process.py official repository unverified MIT (permissive) · c95bb2a25e11fe46 · report
load_tf_weights_in_albert LHRLAB/Text2NKG/transformers/src/transformers/modeling_albert.py official repository unverified MIT (permissive) · 0acb90d02eadd73f · report
process lhrlab/text2nkg/hyperred_data_process.py official repository unverified MIT (permissive) · fccd9efaa74da2dd · report
to_list identical code first harvested elsewhere ran · our draft was wrong fingerprinted licence of this copy not recorded · 9df40357afea56cc · report

Tasks

Event-based N-ary Relaiton ExtractionHyper-Relational ExtractionHypergraph-based N-ary Relaiton ExtractionRole-based N-ary Relaiton Extraction

1 archive task tag without a task page not shown.

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Hyper-Relational Extraction HyperRED Text2NKG Avg. F1 83.81 #1 of 4 Archive leaderboard report

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