SOTAVerified

Relationship Extraction (Distant Supervised)

Relationship extraction is the task of extracting semantic relationships from a text. Extracted relationships usually occur between two or more entities of a certain type (e.g. Person, Organisation, Location) and fall into a number of semantic categories (e.g. married to, employed by, lives in).

Papers

Showing 110 of 19 papers

TitleStatusHype
Statements: Universal Information Extraction from Tables with Large Language Models for ESG KPIsCode1
KGPool: Dynamic Knowledge Graph Context Selection for Relation ExtractionCode1
Improving Distantly-Supervised Relation Extraction through BERT-based Label & Instance EmbeddingsCode1
RECON: Relation Extraction using Knowledge Graph Context in a Graph Neural NetworkCode1
Improving Distantly Supervised Relation Extraction using Word and Entity Based AttentionCode1
Distantly-Supervised Long-Tailed Relation Extraction Using Constraint GraphsCode0
From Bag of Sentences to Document: Distantly Supervised Relation Extraction via Machine Reading ComprehensionCode0
RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side InformationCode0
Learning to Define Terms in the Software Domain0
Neural Relation Extraction via Inner-Sentence Noise Reduction and Transfer Learning0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1KGPOOLP@10%92.3Unverified
2RECONP@10%87.5Unverified
3CGREP@10%84.5Unverified
4BGWAP@10%70.9Unverified
5PCNN+ATTP@10%69.4Unverified
6PCNNP@10%61.3Unverified
7REDSandTAUC0.42Unverified
8BiGRU+WLA+EWAAUC0.39Unverified
9BGRU-SETAUC0.39Unverified
#ModelMetricClaimedVerifiedStatus
1DocDSP@1000.94Unverified