diff --git a/ngrams/term_frequencies.py b/ngrams/term_frequencies.py
index c8c88de..21828a7 100755
--- a/ngrams/term_frequencies.py
+++ b/ngrams/term_frequencies.py
@@ -58,6 +58,7 @@ def my_tokenizer(text, mwe_pass, mwe_tokenize, stopWords):
     # they say that the extract 1-4 grams from 10% of the sentences and then find phrases that appear often relative to the original terms
     # here we take a 10 percent sample of sentences 
     if mwe_pass == 'first':
+        ngram_output = partition.replace("parquet","txt")
         sentences = list(sentences)
         for sentence in sentences:
             if random() <= 0.1: