Papers Relation Extraction
“Relation Extraction” 태그가 달린 논문 2,072편 · 필터 해제
ViTOED: A Dataset for Target-Oriented Emotion Detection on Vietnamese Social Media Texts
This paper introduces ViTOED, a novel dataset for target-oriented emotion detection in Vietnamese social media texts. The ViTOED comprises 10,985 user comments and 21,244 manually annotated opinion quadruples (source, ta…
Relation ExtractionANCHOR-RE: An Agentic Neuro-Symbolic Framework for Grounded Biomedical Relation Extraction
Biomedical relation extraction (BioRE) extracts structured knowledge from biomedical literature for applications such as knowledge base construction and hypothesis generation. Traditional symbolic systems such as SemRep …
Relation ExtractionLA-RL: Label-Aware Self-Reflection for Reinforcement Learning in Information Extraction
Large language models show strong promise for information extraction (IE), but existing reflection-based correction methods are often misaligned with structured extraction outputs. Free-form self-reflection can flag an e…
Information ExtractionReinforcement LearningRelation ExtractionEvent ExtractionLightweight Person-Place Relation Extraction from Historical Newspapers with Dependency Graphs and Proximity Features
The HIPE-2026 shared task introduces person-place relation extraction from multilingual historical newspapers as a new evaluation track, classifying the at and isAt relations between pre-annotated person and location men…
Relation ClassificationRelation ExtractionOntoLearner: A Modular Python Library for Ontology Learning with Large Language Models
Ontology learning (OL) aims to automatically construct structured knowledge models from text, yet progress remains fragmented across methods, domains, and evaluation practices. Despite decades of research, OL lacks a sha…
Relation ExtractionRuleChef: Grounding LLM Task Knowledge in Human-Editable Rules
We present RuleChef, a framework that uses large language models (LLMs) to generate executable rules for NLP tasks such as text classification, Named Entity Recognition (NER), or relation extraction. Rules are generated …
Relation ExtractionText ClassificationCVE-TTP KG: Knowledge Graph Linking Software Vulnerabilities to Attack Behaviors
In the evolving threat landscape, adversaries exploit software vulnerabilities to launch sophisticated attacks, challenging traditional defenses. Although databases like CVE and NVD provide detailed technical information…
Relation ExtractionCross-lingual Relation Extraction with Large Language Models: Zero-Shot, Few-Shot, and Fine-Tuned Evaluation on Romanian
Relation extraction (RE) for low-resource languages is typically constrained by the lack of annotated corpora. We investigate the feasibility of cross-lingual RE for Romanian by combining automatic dataset translation wi…
Relation ClassificationRelation ExtractionDistilledGemma: Balanced Efficiency-Accuracy for Person-Place Relation Extraction from Multilingual Historical Articles
We present DistilledGemma, an efficient and accurate system for the HIPE-2026 shared task on person-place relation extraction from multilingual historical newspaper articles in English, German, and French. Our approach a…
Computational EfficiencyKnowledge DistillationRelation ExtractionPrompt EngineeringLC-ICL: Label-Guided Contrastive In-Context Learning for Robust Information Extraction
There has been increasing interest in exploring the capabilities of advanced large language models (LLMs) in the field of information extraction (IE), specifically focusing on tasks related to named entity recognition (N…
Information ExtractionRelation ExtractionTwo-Stage Prompt Optimization for Few-Shot Relation Extraction: From Reasoning-Guided Search to Gradient-Guided Refinement
Automatic prompt optimization is still underexplored for episodic few-shot relation extraction with smaller language models. We propose a two-stage framework that combines reasoning-based prompt optimization with gradien…
Relation ExtractionReaORE: Reasoning-Guided Progressive Open Relation Extraction Empowered by Large Reasoning Models
Open Relation Extraction (OpenRE) requires a model to extract unseen relations between head and tail entities from unstructured text for real-world applications. The core challenge of OpenRE lies in achieving reliable ge…
Relation ExtractionMapping Political-Elite Networks in Europe with a Multilingual Joint Entity-Relation Extraction Pipeline
Whether political elites organise into rent-seeking coalitions that capture public resources or civic networks that sustain governance is a central question in comparative politics. Yet observing these complex, informal,…
Relation ExtractionEntity ResolutionKnowledge GraphsOverview of HIPE-2026: Person-Place Relation Extraction from Multilingual Historical Texts
Was this person ever at that place, and if so, when? Answering such questions from noisy, multilingual historical documents is the central challenge of HIPE-2026, the third edition of the HIPE evaluation series. Moving f…
Computational EfficiencyDomain GeneralizationRelation ExtractionSub-Billion, Super-Frontier: Small Language Models Rival Zero-Shot Frontier LLMs on General and Literary Relation Extraction
Large language models (LLMs) achieve strong relation extraction (RE), but their computational demands and reliance on proprietary APIs limit deployment in resource-constrained or privacy-sensitive settings. We investigat…
Relation ExtractionNEST: Narrative Event Structures in Time for Long Video Understanding
Recent progress in vision-language models has enabled the processing of increasingly long video sequences, but the ability to handle extended token streams does not translate to understanding of narrative structure in lo…
Relation ExtractionPrompt, Plan, Extract: Zero-Shot Agentic LLMs Workflows for Lung Pathology Extraction from Clinical Narratives
Information extraction from pathology reports is essential for cancer staging, tumor registry population. Yet key data remains embedded in narrative reports, making manual extraction labor-intensive and error-prone. Trad…
Information ExtractionRelation ExtractionIHUBERT: Vector-Based Semantic Deduplication and Domain-Balanced Pretraining for Persian Resources
Persian pretrained language models (PLMs) are still limited by the scarcity of large-scale, high-quality pretraining corpora and by insufficient evaluation beyond standard classification and NER tasks. We present IHUBERT…
Relation ExtractionSentiment AnalysisQuestion AnsweringSAMA: Semantic Anchor-aligned Augmentation for Unified Low-Resource Multimodal Information Extraction
Multimodal Information Extraction (MIE)-covering tasks such as Multimodal Named Entity Recognition (MNER), Relation Extraction (MRE), and Event Extraction (MEE)-is essential for understanding multimedia content but remai…
Information ExtractionRelation ExtractionData AugmentationEvent ExtractionFew-Shot Biomedical Relation Extraction with Large Language Models: A Viable Alternative to Supervised Learning?
Biomedical relation extraction (BioRE) is a key step in transforming biomedical literature into structured knowledge. However, most existing approaches rely on supervised models trained on costly annotated datasets, limi…
Relation Extraction