A large number of datasets and metadata are published via data catalog sites. The availability of metadata properties such as title and description is high, but metadata properties like temporal and spatial coverage are often difficult to obtain. Temporal and spatial coverage are key properties for federated search, but assurance of metadata poses challenges. This study attempts to explore the completion of temporal and spatial coverage in metadata using LLMs and aims to reveal its effectiveness and limitations. Additionally, we propose the "JSON-LD fill-in-the-blank method" as a prompt design for metadata completion.

An overview of the Knowledge Graph Reasoning Challenge for Social Issues held in 2022 will be presented, followed by an introduction to the entries and an evaluation of each.

Wikidata is a large-scale knowledge base which has more than one hundred million items. It is structuralized based on semantic web technologies such as RDF so that they are used as a Knowledge Graph. Wikidata is also linked to Wikipedia in various languages and provides language information for many languages, so it is expected to be used as a large-scale language resource. This paper discusses how Wikidata can be used as a large-scale language resource and introduces the linguistic information extracted from Wikidata.