diff --git a/R/actorizer.R b/R/actorizer.R
index 679df15..8da8569 100644
--- a/R/actorizer.R
+++ b/R/actorizer.R
@@ -7,68 +7,65 @@
 #' @param prefix Regex containing prefixes that should be excluded from hits
 #' @param postfix Regex containing postfixes that should be excluded from hits
 #' @param identifier String used to mark highlights. Should be a lowercase string
-#' @param udmodel The udpipe model used for parsing every hit
 #' @param ver Short string (preferably a single word/sequence) indicating the version of the updated document (i.e. for a udpipe update this string might be 'udV2')
 #' @param es_super Password for write access to ElasticSearch
 #' @return As this is a nested function used within elasticizer, there is no return output
 #' @export
 #' @examples
-#' actorizer(out, localhost = F, ids, type, prefix, postfix, identifier, udmodel, es_super)
-actorizer <- function(out, localhost = F, ids, type, prefix, postfix, identifier, udmodel, es_super, ver) {
+#' actorizer(out, localhost = F, ids, type, prefix, postfix, identifier, es_super)
+actorizer <- function(out, localhost = F, ids, type, prefix, postfix, identifier, es_super, ver) {
+  ### Function to filter out false positives using regex
   exceptionizer <- function(id, ud, doc, markers, regex_identifier, prefix, postfix) {
-    min <- min(ud$start[ud$sentence_id == id])
-    max <- max(ud$end[ud$sentence_id == id])
-    split <- markers[markers %in% seq(min, max, 1)]
-    max <- max+(length(split)*nchar(identifier))
-    sentence <- str_sub(doc$highlight, min, max)
+    min <- min(ud$start[ud$sentence_id == id]) # Get start position of sentence
+    max <- max(ud$end[ud$sentence_id == id]) # Get end position of sentence
+    split <- markers[markers %in% seq(min, max, 1)] # Get markers in sentence
+    max <- max+(length(split)*nchar(identifier)) # Set end position to include markers (e.g if there are two markers of three characters in the sentence, the end position needs to be shifted by +6)
+    sentence <- str_sub(doc$merged, min, max) # Extract sentence from text
+    # Check if none of the regexes match, if so, return sentence id, otherwise (if one of the regexes match) return nothing
     if (!str_detect(sentence, paste0(regex_identifier,postfix)) && !str_detect(sentence, paste0(prefix,regex_identifier))) {
       return(id)
     } else {
       return(NULL)
     }
   }
+  ranger <- function(x, ud) {
+    return(which((ud$start <= x) & (ud$end >= x)))
+  }
   sentencizer <- function(row, out, ids, prefix, postfix, identifier, type) {
-    print(row)
-    ### If no pre or postfixes, match *not nothing* i.e. anything
-    if (is.na(prefix) || prefix == '') {
-      prefix = '$^'
-    }
-    if (is.na(postfix) || postfix == '') {
-      postfix = '$^'
-    }
-    ### Also needs fix for empty strings (non-NA)
-    err <- F
     doc <- out[row,]
+    # Extracting ud output from document
     ud <- doc$`_source.ud`[[1]] %>%
       select(-one_of('exists')) %>% # Removing ud.exists variable
       unnest() %>%
       mutate(doc_id = doc$`_id`)
-    # ud <- as.data.frame(udpipe(udmodel, x = doc$merged, parser = "none", doc_id = doc$`_id`))
-    markers <- doc$markers[[1]][,'start']
-    if (length(setdiff(markers,ud$start)) > 0) {
-      err <- T
-      ud <- ud %>%
-        group_by(doc_id) %>%
-        summarise(
-          sentence_id = list(list(as.integer(0))),
-          sentence_start = list(list(0)),
-          sentence_end = list(list(0))
-        )
-      occurences <- 0
-      prominence <- 0
-      rel_first <- 0
+    markers <- doc$markers[[1]][,'start'] # Extract list of markers
+    # Convert markers to udpipe rows (in some cases the start position doesn't align with the udpipe token start position (e.g. when anti-|||EU is treated as a single word))
+    rows <- unlist(mclapply(markers, ranger, ud = ud, mc.cores = detectCores()))
 
-      return(data.frame(ud,actor_start = I(list(list(markers))), occ = occurences,prom = prominence,rel_first = rel_first, ids = I(list(list(ids))), err = err))
-    }
-    ud$actor[ud$start %in% markers] <- T
-    sentence_count <- length(unique(ud$sentence_id))
-    actor_sentences <- unique(na.omit(ud$sentence_id[ud$actor == T]))
+    # Setting up an actor variable
+    ud$actor <- F
+    ud$actor[rows] <- T
+
+    sentence_count <- max(ud$sentence_id) # Number of sentences in article
+    actor_sentences <- unique(ud$sentence_id[ud$actor]) # Sentence ids of sentences mentioning actor
+    actor_start <- ud$start[ud$actor == T] # Udpipe token start positions for actor
+    actor_end <- ud$end[ud$actor == T] # Udpipe token end positions for actor
+
+    # Conducting regex filtering on matches only when actor type is Party
     if (type == "Party") {
+      ### If no pre or postfixes, match *not nothing* i.e. anything
+      if (is.na(prefix) || prefix == '') {
+        prefix = '$^'
+      }
+      if (is.na(postfix) || postfix == '') {
+        postfix = '$^'
+      }
       sentence_ids <- lapply(actor_sentences, exceptionizer, ud = ud, doc = doc, markers = markers, regex_identifier = regex_identifier, prefix = prefix, postfix = postfix)
     } else {
       sentence_ids <- actor_sentences
     }
 
+    # Generating nested sentence start and end positions for actor sentences
     ud <- ud %>%
       filter(sentence_id %in% sentence_ids) %>%
       group_by(sentence_id) %>%
@@ -79,35 +76,24 @@ actorizer <- function(out, localhost = F, ids, type, prefix, postfix, identifier
       ) %>%
       group_by(doc_id) %>%
       summarise(
-        sentence_id = list(list(as.integer(sentence_id))),
-        sentence_start = list(list(sentence_start)),
-        sentence_end = list(list(sentence_end))
+        sentence_id = list(as.integer(sentence_id)),
+        sentence_start = list(sentence_start),
+        sentence_end = list(sentence_end)
       )
-    occurences <- length(unique(ud$sentence_id[[1]][[1]])) # Number of sentences in which actor occurs
-    prominence <- occurences/sentence_count # Relative prominence of actor in article (number of occurences/total # sentences)
-    rel_first <- 1-(ud$sentence_id[[1]][[1]][1]/sentence_count) # Relative position of first occurence at sentence level
-
-    return(data.frame(ud,actor_start = I(list(list(markers))), occ = occurences,prom = prominence,rel_first = rel_first, ids = I(list(list(ids))), err = err))
-
-
-    # ## The exception below is only valid for the UK, where the original UDPipe output misses a dot at the end of the article, but the actor output does not
-    # ## (UK output is older than actor output, should be updated)
-    # if (length(ud_org$sentence_id) == length(ud$sentence_id)-1) {
-    #   ud <- ud[-length(ud$sentence_id),]
-    # }
-    # if (length(ud_org$sentence_id) == length(ud$sentence_id)) {
-    #   ud <- bind_cols(ud_org, sentence = ud$sentence, token = ud$token, doc_id = ud$doc_id, actor = ud$actor)
-    # } else {
-    #   err = T
-    #   print(paste0('ud_org and ud_actor not the same length for id ', doc$`_id`))
-    #   print(length(ud_org$sentence_id))
-    #   print(length(ud$sentence_id))
-    # }
 
+    return(
+      data.frame(ud, # Sentence id, start and end position for actor sentences
+                 actor_start = I(list(actor_start)), # List of actor ud token start positions
+                 actor_end = I(list(actor_end)), # List of actor ud token end positions
+                 occ = length(unique(actor_sentences)), # Number of sentences in which actor occurs
+                 prom = length(unique(actor_sentences))/sentence_count, # Relative prominence of actor in article (number of occurences/total # sentences)
+                 rel_first = 1-(min(actor_sentences)/sentence_count), # Relative position of first occurence at sentence level
+                 first = min(actor_sentences), # First sentence in which actor is mentioned
+                 ids = I(list(ids)) # List of actor ids
+      )
+    )
   }
   out <- mamlr:::out_parser(out, field = 'highlight', clean = F)
-  # out$highlight <- out$merged
-  # out <- mamlr:::out_parser(out, field = '_source', clean = F)
   offsetter <- function(x) {
     return(x-((row(x)-1)*nchar(identifier)))
   }
@@ -116,7 +102,7 @@ actorizer <- function(out, localhost = F, ids, type, prefix, postfix, identifier
 
   ids <- fromJSON(ids)
   updates <- bind_rows(mclapply(seq(1,length(out[[1]]),1), sentencizer, out = out, ids = ids, postfix = postfix, prefix=prefix, identifier=identifier, type = type, mc.cores = detectCores()))
-  bulk <- apply(updates, 1, bulk_writer, varname ='actorsDetail2', type = 'add', ver = ver)
-  bulk <- c(bulk,apply(updates[c(1,9)], 1, bulk_writer, varname='actors2', type = 'add', ver = ver))
+  bulk <- apply(updates, 1, bulk_writer, varname ='actorsDetail', type = 'add', ver = ver)
+  bulk <- c(bulk,apply(updates[c(1,11)], 1, bulk_writer, varname='actors', type = 'add', ver = ver))
   return(elastic_update(bulk, es_super = es_super, localhost = localhost))
 }
diff --git a/R/bulk_writer.R b/R/bulk_writer.R
index 947538a..11f3a50 100644
--- a/R/bulk_writer.R
+++ b/R/bulk_writer.R
@@ -20,8 +20,8 @@
 bulk_writer <- function(x, index = 'maml', varname, type, ver) {
   ### Create a json object if more than one variable besides _id, otherwise use value as-is
   if (length(x) > 2) {
-    json <- toJSON(bind_rows(x)[-1], collapse = T)
-  x} else {
+    json <- toJSON(list(x[-1]), collapse = T)
+  } else {
     names(x) <- NULL
     json <- toJSON(x[-1], collapse = T)
   }
diff --git a/R/elastic_update.R b/R/elastic_update.R
index fd455c9..96bddc4 100644
--- a/R/elastic_update.R
+++ b/R/elastic_update.R
@@ -30,8 +30,8 @@ elastic_update <- function(x, es_super = 'secret', localhost = T) {
   httr:::stop_for_status(res)
   appData <- httr:::content(res)
   if (appData$errors == T){
-    print(appData)
-    stop("Aborting, errors found during updating")
+    print("Aborting, errors found during updating")
+    return(appData)
   }
   print("updated")
   return(1)
diff --git a/R/ud_update.R b/R/ud_update.R
index d5ba72c..d8632d1 100644
--- a/R/ud_update.R
+++ b/R/ud_update.R
@@ -26,16 +26,16 @@ ud_update <- function(out, localhost = T, udmodel, es_super = .rs.askForPassword
     ud <- as.data.frame(udpipe(udmodel, x = doc$merged, parser = "default", doc_id = doc$`_id`)) %>%
       group_by(doc_id) %>%
       summarise(
-        sentence_id = list(list(as.integer(sentence_id))),
-        token_id = list(list(as.integer(token_id))),
-        lemma = list(list(as.character(lemma))),
-        upos = list(list(as.character(upos))),
-        feats = list(list(as.character(feats))),
-        head_token_id = list(list(as.integer(head_token_id))),
-        dep_rel = list(list(as.character(dep_rel))),
-        start = list(list(as.integer(start))),
-        end = list(list(as.integer(end))),
-        exists = list(list(TRUE))
+        sentence_id = list(as.integer(sentence_id)),
+        token_id = list(as.integer(token_id)),
+        lemma = list(as.character(lemma)),
+        upos = list(as.character(upos)),
+        feats = list(as.character(feats)),
+        head_token_id = list(as.integer(head_token_id)),
+        dep_rel = list(as.character(dep_rel)),
+        start = list(as.integer(start)),
+        end = list(as.integer(end)),
+        exists = list(TRUE)
      )
     return(ud)
   }