SEAL: Self-Evolving Agentic Learning for Conversational Question Answering over Knowledge Graphs

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From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-07-01.)

SEAL: Self-Evolving Agentic Learning for Conversational Question Answering over Knowledge Graphs has 46 facts recorded in Dontopedia across 2 references, with 11 live disagreements.

46 facts·26 predicates·2 sources·11 in dispute

Mostly:has section(6), has potential(3), could push forward(3)

Inbound mentions (22)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

`isSectionOf`Is Section of(6)

Paper Section Conversational Capabilitiesex:paper-section-conversational-capabilities
Paper Section Core Mechanismsex:paper-section-core-mechanisms
Paper Section Experimental Resultsex:paper-section-experimental-results
Paper Section Implicationsex:paper-section-implications
Paper Section Problem Addressedex:paper-section-problem-addressed
Paper Section Seal Framework Introductionex:paper-section-seal-framework-introduction

`couldBenefitFrom`Could Benefit From(3)

Customer Support Botsex:customer-support-bots
Interactive AI Systemsex:interactive-ai-systems
Virtual Assistantsex:virtual-assistants

`outperformedBy`Outperformed by(2)

Non Agentic Baselinesex:non-agentic-baselines
Static Baselinesex:static-baselines

`authored`Authored(1)

Hao Wangex:hao-wang

`authoredPaper`Authored Paper(1)

Paper Authors Sealex:paper-authors-seal

`couldBenefit`Could Benefit(1)

Chat Offer to Delve Deeperex:chat-offer-to-delve-deeper

`demonstratesPerformanceOf`Demonstrates Performance of(1)

Paper Authors Sealex:paper-authors-seal

`discussesPaper`Discusses Paper(1)

Chat Message 2025 12 07 2206ex:chat-message-2025-12-07-2206

`hasTopic`Has Topic(1)

Chat Conversation 2025 12 07ex:chat-conversation-2025-12-07

`isImprovedBy`Is Improved by(1)

Conversational Question Answering System Over Knowledge Graphsex:conversational-question-answering-system-over-knowledge-graphs

`mentions`Mentions(1)

Chat Message 2025 12 07 2206ex:chat-message-2025-12-07-2206

`mentionsPaper`Mentions Paper(1)

Message 2025 12 07 22 05ex:message-2025-12-07-22-05

`proposedIn`Proposed in(1)

Seal Approachex:seal-approach

`targetsPaper`Targets Paper(1)

Request Knowledge Graph Embeddingsex:request-knowledge-graph-embeddings

Other facts (44)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

44 facts

Predicate	Value	Ref
Has Section	Paper Section Problem Addressed	[2]
Has Section	Paper Section Seal Framework Introduction	[2]
Has Section	Paper Section Core Mechanisms	[2]
Has Section	Paper Section Conversational Capabilities	[2]
Has Section	Paper Section Experimental Results	[2]
Has Section	Paper Section Implications	[2]
Has Potential	Virtual Assistants	[2]
Has Potential	Customer Support Bots	[2]
Has Potential	Interactive AI Systems	[2]
Could Push Forward	Virtual Assistants	[2]
Could Push Forward	Customer Support Bots	[2]
Could Push Forward	Interactive AI Systems	[2]
Could Improve Capabilities of	Virtual Assistants	[2]
Could Improve Capabilities of	Customer Support Bots	[2]
Could Improve Capabilities of	Interactive AI Systems	[2]
Rdf:type	Academic Paper	[1]
Rdf:type	Paper	[2]
Compared With	Static Baselines	[2]
Compared With	Non Agentic Baselines	[2]
Has Higher Accuracy Than	Static Baselines	[2]
Has Higher Accuracy Than	Non Agentic Baselines	[2]
Has Higher Robustness Than	Static Baselines	[2]
Has Higher Robustness Than	Non Agentic Baselines	[2]
Demonstrates Performance Metric	Accuracy	[2]
Demonstrates Performance Metric	Robustness	[2]
Outperforms	Static Baselines	[2]
Outperforms	Non Agentic Baselines	[2]
Handles Via Adaptability	User Intent Shifts	[2]
Handles Via Adaptability	Ambiguous Queries	[2]
Has Acronym	Seal Acronym	[2]
Has Author	Hao Wang	[2]
Has Authorship Marker	Et Al Authorship	[2]
Has Authors	Paper Authors Seal	[2]
Has Approach	Seal Approach	[2]
Aims to Improve	Conversational Question Answering System Over Knowledge Graphs	[2]
Addresses Problem	Traditional Kgqa System	[2]
Demonstrates Performance on	Benchmark Cqa Datasets	[2]
Builds Toward	Autonomous Intelligent Conversational Agents	[2]
Reported in	Chat Message 2025 12 07 2206	[2]
Reported by	Omega Bot	[2]
Outlined by	Key Points List	[2]
Is Improvement Target of	Conversational Question Answering System Over Knowledge Graphs	[2]
Has Quality	novel approach	[2]
Proposes Approach	Seal Approach	[2]

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

46 undated

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labelblah/omega/670

SEAL: Self-Evolving Agentic Learning for Conversational Question Answering over Knowledge Graphs

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typeblah/omega/670

ex:AcademicPaper

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typedocument/0098b937-f061-4ef9-8c97-5819e2469534

ex:Paper

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labeldocument/0098b937-f061-4ef9-8c97-5819e2469534

SEAL: Self-Evolving Agentic Learning for Conversational Question Answering over Knowledge Graphs

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hasAcronymdocument/0098b937-f061-4ef9-8c97-5819e2469534

ex:seal-acronym

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hasAuthordocument/0098b937-f061-4ef9-8c97-5819e2469534

ex:hao-wang

—

hasAuthorshipMarkerdocument/0098b937-f061-4ef9-8c97-5819e2469534

ex:et-al-authorship

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hasAuthorsdocument/0098b937-f061-4ef9-8c97-5819e2469534

ex:paper-authors-seal

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hasApproachdocument/0098b937-f061-4ef9-8c97-5819e2469534

ex:seal-approach

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aimsToImprovedocument/0098b937-f061-4ef9-8c97-5819e2469534

ex:conversational-question-answering-system-over-knowledge-graphs

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