SOTAVerified

Knowledge Graphs

A knowledge graph is a structured representation of information that organizes data into nodes (entities) and edges (relationships) to show how different pieces of knowledge are interconnected. It enables enhanced data integration, search, and inference by modeling the relationships between concepts and entities in a graph format.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2501–2525 of 2974 papers

TitleStatusHype
Hierarchical Knowledge Graphs: A Novel Information Representation for Exploratory Search Tasks—0
Knowledge Graph ValidationCode0
ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data—0
Temporal Knowledge Base Completion: New Algorithms and Evaluation ProtocolsCode0
Knowledge Base Completion: Baseline strikes back (Again)Code0
Evaluation Dataset and Methodology for Extracting Application-Specific Taxonomies from the Wikipedia Knowledge Graph—0
A Tree Extension for CoNLL-RDF—0
Enriching Documents with Compact, Representative, Relevant Knowledge GraphsCode0
Self-supervised Knowledge Triplet Learning for Zero-shot Question Answering—0
Cross-lingual Entity Alignment with Incidental SupervisionCode0
Multiple Knowledge GraphDB (MKGDB)—0
Differentiable learning of numerical rules in knowledge graphs—0
KORE 50\^DYWC: An Evaluation Data Set for Entity Linking Based on DBpedia, YAGO, Wikidata, and Crunchbase—0
Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning—0
Exploring the Suitability of Semantic Spaces as Word Association Models for the Extraction of Semantic Relationships—0
Entity Type Prediction in Knowledge Graphs using Embeddings—0
Towards Discourse Parsing-inspired Semantic Storytelling—0
Event-QA: A Dataset for Event-Centric Question Answering over Knowledge Graphs—0
Question Answering over Curated and Open Web Sources—0
Semantic Entity Enrichment by Leveraging Multilingual Descriptions for Link Prediction—0
COVID-19 and Company Knowledge Graphs: Assessing Golden Powers and Economic Impact of Selective Lockdown via AI Reasoning—0
Knowledge-graph based Proactive Dialogue Generation with Improved Meta-Learning—0
Knowledge-guided Deep Reinforcement Learning for Interactive Recommendation—0
Learning Structured Embeddings of Knowledge Graphs with Adversarial Learning Framework—0
Generative Adversarial Zero-shot Learning via Knowledge Graphs—0
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All datasetsMARS (Multimodal Analogical Reasoning dataSet)JerichoWorldWikiKG90M-LSCFB15k

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MarT_MKGformerMRR0.34—Unverified
2MKGformerMRR0.32—Unverified
3MarT_FLAVAMRR0.29—Unverified
4ViLBERTMRR0.29—Unverified
5IKRL (ANALOGY)MRR0.28—Unverified
6IKRLMRR0.27—Unverified
7ViLTMRR0.26—Unverified
8TransAEMRR0.22—Unverified
#ModelMetricClaimedVerifiedStatus
1WorldformerSet accuracy39.15—Unverified
2Q*BERTSet accuracy32.78—Unverified
3GATA-WSet accuracy24.06—Unverified
4WorldformerSet accuracy23.22—Unverified
5Seq2SeqSet accuracy14.29—Unverified
6RulesSet accuracy4.7—Unverified
#ModelMetricClaimedVerifiedStatus
1TransE-ConcatTest MRR85.48—Unverified
2ComplEx-ConcatTest MRR0.86—Unverified
3ComplEx-RoBERTaTest MRR0.72—Unverified
4TransE-RoBERTaTest MRR0.63—Unverified
#ModelMetricClaimedVerifiedStatus
1COMPLEXMRR0.59—Unverified