Semantic embeddings for every unique word item definition, computed with
Google's multilingual gemini-embedding-001 model (768 dimensions).
All languages share one embedding space, so cosine similarities are
meaningful both within and across languages.
Usage
get_embeddings(language = NULL, version = "current")
Arguments
- language
An optional string specifying which language's embeddings
to retrieve.
- version
A string specifying which version of the Wordbank dataset
to use, e.g. "v1.2" to pin a released version for reproducibility.
Defaults to "current", the most recent release.
Value
A data frame with one row per unique item definition:
language, item_definition, embedding (a
list-column of numeric vectors), and dataset_version.
Examples
if (FALSE) { # \dontrun{
danish_embeddings <- get_embeddings(language = "Danish")
} # }