diff --git a/R/duplicate_detection.R b/R/dupe_detect.R
similarity index 90%
rename from R/duplicate_detection.R
rename to R/dupe_detect.R
index ff69b81..5ced5fb 100644
--- a/R/duplicate_detection.R
+++ b/R/dupe_detect.R
@@ -5,7 +5,7 @@
 #' @param grid A cross-table of all possible combinations of doctypes and dates
 #' @param cutoff Cutoff value for cosine similarity above which documents are considered duplicates
 #' @param es_pwd Password for Elasticsearch read access
-#' @return dupe_objects.json (containing each id and all its duplicates) and remove_ids.txt (list of ids to be removed) in current working directory
+#' @return dupe_objects.json and data frame containing each id and all its duplicates. remove_ids.txt and character vector with list of ids to be removed. Files are in current working directory
 #' @export
 #' @examples
 #' dupe_detect(1,grid,es_pwd)
@@ -45,6 +45,7 @@ dupe_detect <- function(row, grid, cutoff, es_pwd) {
   write(unique(rownames(which(simil >= cutoff, arr.ind = TRUE))),
         file = paste0(getwd(),'/remove_ids.txt'),
         append=T)
+  return(list(df,unique(rownames(which(simil >= cutoff, arr.ind = TRUE)))))
   ### Dummy code to verify that filtering out unique ids using the bottom half of the matrix actually works
   # id_filter <- unique(rownames(which(simil >= cutoff, arr.ind = TRUE)))
   # dfm_nodupes <- dfm_subset(dfm, !(docnames(dfm) %in% id_filter))
diff --git a/man/dupe_detect.Rd b/man/dupe_detect.Rd
index 13209bd..03710b5 100644
--- a/man/dupe_detect.Rd
+++ b/man/dupe_detect.Rd
@@ -16,7 +16,7 @@ dupe_detect(row, grid, cutoff, es_pwd)
 \item{es_pwd}{Password for Elasticsearch read access}
 }
 \value{
-dupe_objects.json (containing each id and all its duplicates) and remove_ids.txt (list of ids to be removed) in current working directory
+dupe_objects.json and data frame containing each id and all its duplicates. remove_ids.txt and character vector with list of ids to be removed. Files are in current working directory
 }
 \description{
 Get ids of duplicate documents that have a cosine similarity score higher than [threshold]