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Found 5 papers, 1 papers with code
Relations Prediction for Knowledge Graph Completion using Large Language Models
In this work, we make use of the knowledge graph node names to fine-tune a large language model for the relation prediction task.
Subgraph2vec: A random walk-based algorithm for embedding knowledge graphs
However, most of these methods require high levels of computational time and space.
Knowledge Graph Completion using Structural and Textual Embeddings
We demonstrate that our model achieves competitive results in the relation prediction task when evaluated on a widely used dataset.
A Few-Shot Learning Focused Survey on Recent Named Entity Recognition and Relation Classification Methods
Named Entity Recognition (NER) and Relation Classification (RC) are important steps in extracting information from unstructured text and formatting it into a machine-readable format.
ES-LDA: Entity Summarization using Knowledge-based Topic Modeling
With the advent of the Internet, the amount of Semantic Web documents that describe real-world entities and their inter-links as a set of statements have grown considerably.
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