tBiodivL: Larger Semantic Table Annotations Benchmark for Biodiversity Domain

tBiodivL is a dataset for tabular data to knowledge graph matching. It is derived from the Biodiversity domain and has two types of tables. On the one hand, Horizontal Relational Tables are where each table represents a collection of entities. On the other hand, Entity Tables represent a single entity. We supported ground truth data from Wikidata as a target knowledge graph (KG). tBiodivL is generated by KG2Tables using 10 levels of a recursive hierarchy of related concepts in Wikidata. It is the successor work of tBiodiv tBiodivL contains 222,353 entity and horizontal tables, while this repository contains only a sample of 1% of the total generated tables of the entire benchmark with its ground truth data (gt). The Full size of this dataset is 312 GB. We will update this repository with the full dataset in the Future. Please get in touch if you are interested in the full dataset, The supported tasks for semantic table annotations are: Topic Detection (TD) links the entire table to an entity or a class from the target KG. Cell Entity Annotation (CEA) maps individual table cells to entities from the target KG. Column Type Annotation (CTA) links individual table columns to classes from the target KG. Column Property Annotation (CPA) detects the relations between column pairs from the target knowledge graph. Row Annotation (RA) annotates the entire row to a KG entity or property.tBiodivL是一款面向表格数据与知识图谱匹配（tabular data to knowledge graph matching）的数据集，源自生物多样性领域，包含两类表格。其一为横向关系表（Horizontal Relational Tables）：每张表代表一组实体集合；其二为实体表（Entity Tables）：每张表仅对应单个实体。本数据集以维基数据（Wikidata）的基准真值（ground truth）数据作为目标知识图谱（Knowledge Graph, KG）的标注基准。 tBiodivL由KG2Tables基于维基数据中关联概念的10层递归层级结构生成，是tBiodiv的后续研究工作。 该数据集总计包含222,353张实体表与横向关系表，但当前本仓库仅提供了全部基准数据集1%的样本及其基准真值（ground truth，简称gt）数据。该数据集完整体量达312 GB，我们将于未来更新本仓库以上传完整数据集。若您对完整数据集感兴趣，可与我们取得联系。 本数据集支持的语义表格标注任务包括： - 主题检测（Topic Detection, TD）：将整张表格链接至目标知识图谱中的实体或类别； - 单元格实体标注（Cell Entity Annotation, CEA）：将单个表格单元格映射至目标知识图谱中的实体； - 列类型标注（Column Type Annotation, CTA）：将单个表格列链接至目标知识图谱中的类别； - 列属性标注（Column Property Annotation, CPA）：检测目标知识图谱中列对之间的关联关系； - 行标注（Row Annotation, RA）：将整行内容标注为知识图谱中的实体或属性。