Papers with entity alignment method

3 papers
DeepAlignment: Unsupervised Ontology Matching with Refined Word Vectors (N18-1)

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Challenge: Ontologies compartmentalize types and relations in a domain and require a process to establish alignments between entities to unify and extend existing knowledge.
Approach: They propose a method which refines pre-trained word vectors to derivate ontological entity descriptions tailored to the ontology matching task.
Outcome: The proposed method improves ontology matching performance over the current state-of-the-art.
NALA: an Effective and Interpretable Entity Alignment Method (2024.findings-emnlp)

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Challenge: Existing embedding-based EA methods encode entities as embeddables and learn to align embeddibles.
Approach: They propose to capture three types of logical inference paths with Non-Axiomatic Logic to iteratively align entities and relations by integrating the conclusions of the inference path.
Outcome: The proposed method outperforms state-of-the-art methods in terms of Hits@1 on all three datasets of DBP15K with both supervised and unsupervised settings.
Entity Profile Generation and Reasoning with LLMs for Entity Alignment (2025.findings-emnlp)

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Challenge: Entity alignment is a process of identifying and linking equivalent entities across knowledge graphs . only a small fraction of these entities are aligned .
Approach: They propose a method that combines large language models with entity embeddings to align entities.
Outcome: ProLEA is a method that combines large language models with entity embeddings to improve alignment accuracy, robustness, and explainability.

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