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This repository hosts a comprehensive suite for graph-based entity summarization dataset generating from user-selected Wikipedia pages. Utilizing a series of interconnected modules, it leverages Wikidata and Wikipedia dumps to construct a dataset, alongside auto-generated ground truths.
Graph Attention Networks for Entity Summarization is the model that applies deep learning on graphs and ensemble learning on entity summarization tasks.
ESLM: An approach to improve the performance of entity summarization by leveraging language models and enrichment language model using knowledge graph embedding
ESBM (short for Entity Summarization BenchMark) is a benchmark for evaluating algorithms for entity summarization, aka entity summarizers. This is an old repository for the ESBM benchmark, for more updated information, see