OC-782K: Knowledge Graph of "Scientometrics" modelled according to the OpenCitations Data Model

<p>This dataset is a knowledge graph extracted from a&nbsp;<a href="https://static.aminer.cn/misc/na-data-kdd18.zip">t</a>riplestore covering information about the journal <em>Scientometrics</em>&nbsp;and modelled according to the OpenCitations Data Model. The original triplestore is available <a href="https://doi.org/10.5281/zenodo.5151264">here</a>. This KG was extracted&nbsp;for a research project on knowledge graph embeddings (KGEs)&nbsp;for author disambiguation. Structural triples of the knowledge graph are split into training, testing and validation for applying representation learning methods. Textual literals and numeric literals were stored separately in order to implement multimodal approaches for KGEs (see&nbsp;<a href="https://arxiv.org/abs/1802.00934">arXiv:1802.00934</a>). For the same reason, textual literals and numeric literals are already stored into sentence embeddings and a&nbsp;numeric matrix&nbsp;respectively in the files&nbsp;<em>textual_literals.npy&nbsp;</em>and&nbsp;<em>numeric_literals.npy</em>. The file <em>and_eval</em><em>.json&nbsp;</em>contains the evaluation dataset used for evaluating our AND architecture. For the script used to gather this dataset see the GitHub repository:&nbsp;<a href="https://github.com/sntcristian/and-kge/tree/main/aminer">https://github.com/sntcristian/and-kge/tree/main/open-citations</a>.</p>