Wikidata Thematic Subgraph Selection - An Artwork Dataset for experiments

Description This dataset complements the two previously released datasets for Wikidata Thematic Subgraph Selection. It introduces a new domain, with entities within the field of Art and Works of Art to support the experiments described in the paper Relevant Entity Selection: Knowledge Graph Bootstrapping via Zero-Shot Analogical Pruning. Specifically, this dataset was built starting from a set of seed QIDs of interest from the domain of Art and Works of Art. A graph expansion is performed following edges in Wikidata. Traversed entities and classes that thematically deviates from seed QIDs of interest should be pruned. The dataset thus consists of annotated pairs of entities (seed, neighbor), identified by their Wikidata QIDs, along with a binary decision: "keep" or "prune". Statistics Here you can find key statistics about the dataset. # Seed QIDs # Labeled decisions # Prune decisions Min prune depth Max prune depth # Keep decisions Min keep depth Max keep depth # Reached nodes 27 2111 1178 1 5 933 1 5 4363 Resources Similarly to the previoulsy published datasets, this resource includes the following files: datasetX.csv: Contains one seed entity per line. datasetX_labels.csv: Lists each seed entity along with its corresponding label. datasetX_gold_decisions.csv: Provides pairs of seed and reached entities, with a binary decision label (1 = keep, 0 = prune). datasetX_Y_folds.pkl: Contains stratified folds for implementing cross-validation.