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 1–10 of 19 papers

TitleStatusHype
Improving Distantly Supervised Relation Extraction using Word and Entity Based AttentionCode1
Improving Distantly-Supervised Relation Extraction through BERT-based Label & Instance EmbeddingsCode1
Statements: Universal Information Extraction from Tables with Large Language Models for ESG KPIsCode1
RECON: Relation Extraction using Knowledge Graph Context in a Graph Neural NetworkCode1
KGPool: Dynamic Knowledge Graph Context Selection for Relation ExtractionCode1
Visualization of Clandestine Labs from Seizure Reports: Thematic Mapping and Data Mining Research Directions—0
Cross-Corpus Training with TreeLSTM for the Extraction of Biomedical Relationships from Text—0
Learning to Define Terms in the Software Domain—0
Neural Relation Extraction via Inner-Sentence Noise Reduction and Transfer Learning—0
Research Project: Text Engineering Tool for Ontological Scientometry—0
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Benchmark Results

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