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
Improving Distantly-Supervised Relation Extraction through BERT-based Label & Instance EmbeddingsCode1
RECON: Relation Extraction using Knowledge Graph Context in a Graph Neural NetworkCode1
KGPool: Dynamic Knowledge Graph Context Selection for Relation ExtractionCode1
Statements: Universal Information Extraction from Tables with Large Language Models for ESG KPIsCode1
Improving Distantly Supervised Relation Extraction using Word and Entity Based AttentionCode1
Neural Relation Extraction with Selective Attention over InstancesCode0
Distant Supervision for Relation Extraction via Piecewise Convolutional Neural NetworksCode0
From Bag of Sentences to Document: Distantly Supervised Relation Extraction via Machine Reading ComprehensionCode0
RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side InformationCode0
Joint Bootstrapping Machines for High Confidence Relation ExtractionCode0
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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