Classify spec variables — classify_variables • admiralagent

Translates each spec variable's free-text derivation into a variable IR using the selected backend: `"rules"` runs the built-in deterministic, zero-dependency keyword classifier (baseline and fallback); `"llm"` runs the structured-extraction pipeline via [classify_variables_llm()] (requires an ellmer `chat`).

Usage

classify_variables(
  spec,
  dataset,
  backend = c("rules", "llm"),
  chat = NULL,
  samples = 1,
  consensus = c("majority", "first"),
  prompt_variant = c("full", "neutral", "minimal")
)

Arguments

spec: Spec data frame compatible with [read_spec_df()].
dataset: Dataset name to classify (e.g. `"ADSL"`).
backend: One of `"rules"` or `"llm"`.
chat: ellmer chat object; required when `backend = "llm"`, ignored otherwise.
samples: Number of independent LLM pipeline runs; used when `backend = "llm"`, ignored otherwise. See [classify_variables_llm()].
consensus: Voting strategy across samples; used when `backend = "llm"`, ignored otherwise. See [classify_variables_llm()].
prompt_variant: System prompt variant; used when `backend = "llm"`, ignored otherwise. See [classify_variables_llm()].

Value

List of `aa_variable_ir` objects, one per spec variable.

Details

Classify spec variables into layer IR

Examples

spec <- mock_spec_adsl()
ir <- classify_variables(spec, "ADSL", backend = "rules")
ir[[1]]$variable
#> [1] "STUDYID"