Embedding Cultural Heritage Metadata: Pipeline Design, Multilingual Retrieval, and Hybrid Search in LinkedCulture

This paper describes the implementation behind LinkedCulture, an experimental cross-institutional cultural heritage retrieval prototype. It explains how structured cultural heritage metadata is translated into embeddable prose, how records from eight institutions are normalized into a canonical schema, how OpenSearch and Qdrant support keyword and semantic retrieval, and how Reciprocal Rank Fusion combines the two ranking signals. The paper documents a transition from English-centered to multilingual embedding prompted by an observed cross-language retrieval failure, and reports preliminary observations on cross-lingual retrieval behavior in the extended index. It also examines where pipeline design choices introduce potential bias, where embedding models fail in predictable ways, and how metadata density, institutional imbalance, licensing constraints, and local infrastructure choices shape retrieval behavior. This is the second paper in the LinkedCulture research paper series.