SemTab 24: Semantic Table Annotations Benchmark for LLM-based approaches

SuperSemtab24 is a dataset for tabular data to knowledge graph matching. The dataset is divided into training and validation sets. The dataset includes general-purpose tables and intentionally misspelled entities to evaluate the model's robustness. Participants must annotate the entity mentions in the validation set and submit their annotations (following a target file). The repository contains the full version of the dataset; the ground truth (GT) of the test set will be uploaded in the future.