Joint Entity and Relation Extraction
Scores reported from systems which jointly extract entities and relations.
Leaderboards
| TREND | DATASET | BEST METHOD | PAPER TITLE | PAPER | CODE | COMPARE |
|---|---|---|---|---|---|---|
|
Greatest papers with code
CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases
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 type labels into two low-dimensional spaces (for entity and relation mentions respectively), where, in each space, objects whose types are close will also have similar representations.
Adversarial training for multi-context joint entity and relation extraction
EMNLP 2018
• bekou/multihead_joint_entity_relation_extraction
• 
Adversarial training (AT) is a regularization method that can be used to improve the robustness of neural network methods by adding small perturbations in the training data.
#3 best model for
Relation Extraction
on ADE Corpus
GraphRel: Modeling Text as Relational Graphs for Joint Entity and Relation Extraction
ACL 2019
• tsujuifu/pytorch_graph-rel
• 
In contrast to previous baselines, we consider the interaction between named entities and relations via a 2nd-phase relation-weighted GCN to better extract relations.
#6 best model for
Relation Extraction
on WebNLG
Span-based Joint Entity and Relation Extraction with Transformer Pre-training
The model is trained using strong within-sentence negative samples, which are efficiently extracted in a single BERT pass.
SOTA for Relation Extraction on CoNLL04
JOINT ENTITY AND RELATION EXTRACTION NAMED ENTITY RECOGNITION RELATION CLASSIFICATION
Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme
ACL 2017
• tonygsw/Joint-Extraction-of-Entities-and-Relations-Based-on-a-Novel-Tagging-Scheme
•
Joint extraction of entities and relations is an important task in information extraction.
#3 best model for
Relation Extraction
on NYT-single
Entity, Relation, and Event Extraction with Contextualized Span Representations
IJCNLP 2019
• dwadden/dygiepp
•
We examine the capabilities of a unified, multi-task framework for three information extraction tasks: named entity recognition, relation extraction, and event extraction.
#2 best model for
Joint Entity and Relation Extraction
on SciERC
JOINT ENTITY AND RELATION EXTRACTION NAMED ENTITY RECOGNITION RELATION EXTRACTION
A General Framework for Information Extraction using Dynamic Span Graphs
We introduce a general framework for several information extraction tasks that share span representations using dynamically constructed span graphs.
SOTA for Relation Extraction on ACE 2005
JOINT ENTITY AND RELATION EXTRACTION NAMED ENTITY RECOGNITION RELATION EXTRACTION
Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction
We introduce a multi-task setup of identifying and classifying entities, relations, and coreference clusters in scientific articles.
#4 best model for
Joint Entity and Relation Extraction
on SciERC
COREFERENCE RESOLUTION GRAPH CONSTRUCTION JOINT ENTITY AND RELATION EXTRACTION NAMED ENTITY RECOGNITION
Effective Modeling of Encoder-Decoder Architecture for Joint Entity and Relation Extraction
• nusnlp/PtrNetDecoding4JERE
•
A relation tuple consists of two entities and the relation between them, and often such tuples are found in unstructured text.
#4 best model for
Relation Extraction
on NYT
JOINT ENTITY AND RELATION EXTRACTION MACHINE TRANSLATION RELATION EXTRACTION
Table Filling Multi-Task Recurrent Neural Network for Joint Entity and Relation Extraction
COLING 2016
• pgcool/TF-MTRNN
•
This paper proposes a novel context-aware joint entity and word-level relation extraction approach through semantic composition of words, introducing a Table Filling Multi-Task Recurrent Neural Network (TF-MTRNN) model that reduces the entity recognition and relation classification tasks to a table-filling problem and models their interdependencies.
ENTITY EXTRACTION JOINT ENTITY AND RELATION EXTRACTION RELATION CLASSIFICATION SEMANTIC COMPOSITION STRUCTURED PREDICTION