tBiomed: Semantic Table Annotations Benchmark for Biomedical Domain
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tBiomed is a dataset for tabular data to knowledge graph matching. It is derived for 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). tBiomed is generated by KG2Tables using two levels of a recursive hierarchy of related concepts in Wikidata. tBiomed contains 26,778 entity and horizontal tables, while this repository contains only a validation fold of the original data representing 20% of the total of the entire benchmark with its ground truth data (gt). The Full size of this dataset is 1 GB. We will update this repository with the full dataset, including the test fold with its ground truth data 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.
tBiomed是一款面向表格数据与知识图谱匹配任务的数据集，面向生物多样性领域构建，包含两类表格。其一为横向关系表格（Horizontal Relational Tables）：每张表格代表一组实体集合；其二为实体表格（Entity Tables）：每张表格仅对应单个实体。本数据集以维基数据（Wikidata）中的标注真值数据作为目标知识图谱（Knowledge Graph，简称KG）。tBiomed由KG2Tables基于维基数据中关联概念的两层递归层级结构生成，总计包含26778张实体表格与横向关系表格。当前本代码仓库仅收录原始数据集的验证折（validation fold），其规模占完整基准数据集的20%，并附带对应的标注真值数据（ground truth，简称gt）。该数据集的完整体积为1吉字节（GB）。本团队后续将更新本代码仓库，上传包含测试折（test fold）及其标注真值数据的完整数据集。若您希望获取完整数据集，可与我们联系。本数据集支持的语义表格标注任务包括：主题检测（Topic Detection，简称TD）将整张表格与目标知识图谱中的实体或类别进行关联；单元格实体标注（Cell Entity Annotation，简称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，简称CTA）将单个表格列与目标知识图谱中的类别进行关联；列属性标注（Column Property Annotation，简称CPA）识别目标知识图谱中列对之间的关联关系；行标注（Row Annotation，简称RA）将整行表格标注为目标知识图谱中的实体或属性。
