Collapses a character vector to its distinct non-blank texts, keeping the order of first appearance and counting how often each text occurred. Embedding and clustering operate on the distinct texts (so repeated templates cannot drag the cluster geometry), while the returned counts carry the original frequencies back into reporting, for example through [topic_sizes()].
Value
A base data frame with one row per distinct text and columns `text` (in order of first appearance) and `n` (number of occurrences).
Examples
dedupe(c("Very good!", "Try again.", "Very good!", NA, " "))
#> text n
#> 1 Very good! 2
#> 2 Try again. 1
