Small fixes for refactor by @proycon

README.md

@@ -26,6 +26,6 @@ Example usage
 
 Glem comes with a pretrained model, based on lemmas chosen by humans (in the UiO PROIEL project, PI: Dag Haug), for Herodotus. If you are inside the Lamachine environment (something like ```lamachine/bin/activate```), you can use it (with or without Frog) as follows:
 
-```glem -f input.txt -m herodotus```
+```glem -f input.txt```
 
 The files for this model can be found in ```glem/pretrained_models/herodotus``` .

glem/glem.py

@@ -110,7 +110,7 @@ def lemmatise(word, tag, ghd_words, verbose):
         print( "UNKNOWN WORD", word )
     return (None, "UNKNOWN")
 
-def query_frog_sentence(words, verbose):
+def query_frog_sentence(frog,words, verbose):
     if have_frog:
         try:
             frog_out  = frog.process(words)
@@ -501,7 +501,7 @@ def main():
                             words.pop(0)
                         words = [ normalize('NFC', w) for w in words ]
                         if have_frog:
-                            frog_out = query_frog_sentence(" ".join(words) , verbose)
+                            frog_out = query_frog_sentence(frog," ".join(words) , verbose)
                         for word in words:
                             if verbose:
                                 print( "\n", word, lcount, wcount )