Research software · R package
Get name-based predictions in R.
We built nomine to call NamePrism and NamSor from R and bring their predictions back into a data frame.
Initial versions: entirely human-created. AI was used only for later updates and code fixes.
Quick start
install.packages("remotes")
remotes::install_github("lobsterbush/nomine")
library(nomine)
# Store your provider credentials in environment variables.
get_ethnicities(
c("Charles Crabtree", "Volha Chykina"),
t = Sys.getenv("NAMEPRISM_TOKEN")
)API examples require your own credentials and a network connection. Obtain credentials from NamePrism or NamSor; consult the provider for current access terms.
Choose the classifier
| Task | Function | Provider |
|---|---|---|
| Probabilities over six U.S. ethnicity categories | get_ethnicities() |
NamePrism |
| Probabilities over leaf nationality categories | get_nationalities() |
NamePrism |
| Gender classification from given and family names | get_gender() |
NamSor |
get_gender(
given = c("Charles", "Volha"),
family = c("Crabtree", "Chykina"),
api_key = Sys.getenv("NAMSOR_API_KEY")
)These are predictions based on names. A person’s own account of their identity can differ. I’d read the returned probabilities alongside the provider’s categories before deciding how to use them. The function help explains the columns and what happens when a request fails.
Provenance
Human – AI (editor) 👤✏️🤖
We wrote every initial version ourselves, without AI. We’ve used AI only for later updates and code fixes. I’m Charles Crabtree, and this is my account of how the package was made.
The label and mark follow The Latent Review’s provenance standard, shared under CC BY 4.0. The software remains MIT licensed.
Help and development
If something isn’t working, please tell us in the issue tracker. The source and README include installation requirements and local documentation build instructions.