Wikidata Thematic Subgraph Selection - An Artwork Dataset for experiments
Authors/Creators
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1.
Université de Lorraine
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2.
French National Center for Scientific Research (head office)
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3.
Laboratoire Lorrain de Recherche en Informatique et ses Applications
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4.
Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento
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5.
Instituto Superior Técnico
- 6. Universidade de Lisboa
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7.
Université Côte d'Azur
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8.
National Institute for Research in Computer and Control Sciences
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9.
Centre Inria d'Université Côte d'Azur
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10.
Laboratoire d'Informatique, Signaux et Systèmes de Sophia Antipolis
Description
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:
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datasetX.csv: Contains one seed entity per line.
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datasetX_labels.csv: Lists each seed entity along with its corresponding label.
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datasetX_gold_decisions.csv: Provides pairs of seed and reached entities, with a binary decision label (1 = keep, 0 = prune).
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datasetX_Y_folds.pkl: Contains stratified folds for implementing cross-validation.
Files
dataset3.zip
Files
(31.2 kB)
| Name | Size | Download all |
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md5:a7dfd7db1ecaf9ae06039ebc357d7b8d
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Additional details
Related works
- Is supplement to
- Conference paper: 10.1145/3583780.3615030 (DOI)
- Conference paper: arXiv:2306.16296 (arXiv)
- Dataset: 10.5281/zenodo.8091583 (DOI)
Funding
- Agence Nationale de la Recherche
- AT2TA - AT2TA - Analogies: from Theory to Tools and Applications ANR-22-CE23-0023