Joint Entity and Relation Extraction

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

16 leaderboard tables shown for this task, 16 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 16 until expanded.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

16 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 56 papers with code (87 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction
  29 Aug 2018 5 repositories listed
  We introduce a multi-task setup of identifying and classifying entities, relations, and coreference clusters in scientific articles.
• Entity, Relation, and Event Extraction with Contextualized Span Representations
  8 Sep 2019 4 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  We examine the capabilities of a unified, multi-task framework for three information extraction tasks: named entity recognition, relation extraction, and event extraction.
• Span-based Joint Entity and Relation Extraction with Transformer Pre-training
  17 Sep 2019 3 repositories listed
  The model is trained using strong within-sentence negative samples, which are efficiently extracted in a single BERT pass.
• A General Framework for Information Extraction using Dynamic Span Graphs
  5 Apr 2019 3 repositories listed
  We introduce a general framework for several information extraction tasks that share span representations using dynamically constructed span graphs.
• CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases
  27 Oct 2016 3 repositories listed
  We propose a novel domain-independent framework, called CoType, that runs a data-driven text segmentation algorithm to extract entity mentions, and jointly embeds entity mentions, relation mentions, text features and…
• A sequence-to-sequence approach for document-level relation extraction
  3 Apr 2022 2 repositories listed
  In this paper, we develop a sequence-to-sequence approach, seq2rel, that can learn the subtasks of DocRE (entity extraction, coreference resolution and relation extraction) end-to-end, replacing a pipeline of…
• Packed Levitated Marker for Entity and Relation Extraction
  13 Sep 2021 2 repositories listed Syntology ran 3 of 9 samples · 6 unverified · 1 pointer-only (licence)
  In particular, we propose a neighborhood-oriented packing strategy, which considers the neighbor spans integrally to better model the entity boundary information.
• Structured Prediction as Translation between Augmented Natural Languages
  14 Jan 2021 2 repositories listed
  We propose a new framework, Translation between Augmented Natural Languages (TANL), to solve many structured prediction language tasks including joint entity and relation extraction, nested named entity recognition,…
• A Frustratingly Easy Approach for Entity and Relation Extraction
  24 Oct 2020 2 repositories listed Syntology ran 3 of 4 samples · 1 unverified · 1 pointer-only (licence)
  Our approach essentially builds on two independent encoders and merely uses the entity model to construct the input for the relation model.
• Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoders
  8 Oct 2020 2 repositories listed Syntology ran 0 of 3 samples · 3 unverified · 3 pointer-only (licence)
  In this work, we propose the novel {\em table-sequence encoders} where two different encoders -- a table encoder and a sequence encoder are designed to help each other in the representation learning process.
• Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme
  7 Jun 2017 2 repositories listed
  Joint extraction of entities and relations is an important task in information extraction.
• REXEL: An End-to-end Model for Document-Level Relation Extraction and Entity Linking
  19 Apr 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverified
  Extracting structured information from unstructured text is critical for many downstream NLP applications and is traditionally achieved by closed information extraction (cIE).
• EnriCo: Enriched Representation and Globally Constrained Inference for Entity and Relation Extraction
  18 Apr 2024 1 repository listed
  Joint entity and relation extraction plays a pivotal role in various applications, notably in the construction of knowledge graphs.
• GraphER: A Structure-aware Text-to-Graph Model for Entity and Relation Extraction
  18 Apr 2024 1 repository listed
  Information extraction (IE) is an important task in Natural Language Processing (NLP), involving the extraction of named entities and their relationships from unstructured text.
• An Autoregressive Text-to-Graph Framework for Joint Entity and Relation Extraction
  2 Jan 2024 1 repository listed Syntology ran 7 of 7 samples · 0 unverified · 7 pointer-only (licence)
  In this paper, we propose a novel method for joint entity and relation extraction from unstructured text by framing it as a conditional sequence generation problem.
• Joint Entity and Relation Extraction with Span Pruning and Hypergraph Neural Networks
  26 Oct 2023 1 repository listed
  Also, most of current ERE models do not take into account higher-order interactions between multiple entities and relations, while higher-order modeling could be beneficial.
• Distantly-Supervised Joint Extraction with Noise-Robust Learning
  8 Oct 2023 1 repository listed
  Joint entity and relation extraction is a process that identifies entity pairs and their relations using a single model.
• CARE: Co-Attention Network for Joint Entity and Relation Extraction
  24 Aug 2023 1 repository listed
  However, most existing joint extraction methods suffer from issues of feature confusion or inadequate interaction between the two subtasks.
• Similarity-based Memory Enhanced Joint Entity and Relation Extraction
  14 Jul 2023 1 repository listed
  Document-level joint entity and relation extraction is a challenging information extraction problem that requires a unified approach where a single neural network performs four sub-tasks: mention detection, coreference…
• End-to-End Temporal Relation Extraction in the Clinical Domain
  2 Apr 2023 1 repository listed
  Temporal relation extraction is an important task in the clinical domain, as it allows a better understanding of the temporal context of clinical events.
• DocRED-FE: A Document-Level Fine-Grained Entity And Relation Extraction Dataset
  20 Mar 2023 1 repository listed
  Joint entity and relation extraction (JERE) is one of the most important tasks in information extraction.
• Knowledge Graph Generation From Text
  18 Nov 2022 1 repository listed
  In this work we propose a novel end-to-end multi-stage Knowledge Graph (KG) generation system from textual inputs, separating the overall process into two stages.
• KPI-EDGAR: A Novel Dataset and Accompanying Metric for Relation Extraction from Financial Documents
  17 Oct 2022 1 repository listed
  We introduce KPI-EDGAR, a novel dataset for Joint Named Entity Recognition and Relation Extraction building on financial reports uploaded to the Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system, where…
• JBNU-CCLab at SemEval-2022 Task 12: Machine Reading Comprehension and Span Pair Classification for Linking Mathematical Symbols to Their Descriptions
  1 Jul 2022 1 repository listed
  This paper describes our system in the SemEval-2022 Task 12: ‘linking mathematical symbols to their descriptions’, achieving first on the leaderboard for all the subtasks comprising named entity extraction (NER) and…
• AIFB-WebScience at SemEval-2022 Task 12: Relation Extraction First - Using Relation Extraction to Identify Entities
  1 Jul 2022 1 repository listed
  In this paper, we present an end-to-end joint entity and relation extraction approach based on transformer-based language models.
• EmRel: Joint Representation of Entities and Embedded Relations for Multi-triple Extraction
  1 Jul 2022 1 repository listed
  Multi-triple extraction is a challenging task due to the existence of informative inter-triple correlations, and consequently rich interactions across the constituent entities and relations.
• SciDeBERTa: Learning DeBERTa for Science Technology Documents and Fine-Tuning Information Extraction Tasks
  8 Jun 2022 1 repository listed
  Experiments verified that SciDeBERTa(CS) continually pre-trained in the computer science domain achieved 3.
• DeepStruct: Pretraining of Language Models for Structure Prediction
  21 May 2022 1 repository listed Syntology ran 7 of 13 samples · 6 unverified
  We introduce a method for improving the structural understanding abilities of language models.
• Joint Entity and Relation Extraction Based on Table Labeling Using Convolutional Neural Networks
  1 May 2022 1 repository listed
  We adopt table representations to model the entities and relations, casting the entity and relation extraction as a table-labeling problem.
• AIFB-WebScience at SemEval-2022 Task 12: Relation Extraction First -- Using Relation Extraction to Identify Entities
  10 Mar 2022 1 repository listed
  In this paper, we present an end-to-end joint entity and relation extraction approach based on transformer-based language models.

Syntology lines on 7 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.