Bugfix.

src/lambo/resources/languages.txt

@@ -3,7 +3,7 @@ UD_Afrikaans-AfriBooms af Afrikaans
 UD_Ancient_Greek-PROIEL ? Ancient_Greek *
 UD_Ancient_Greek-Perseus ? Ancient_Greek
 UD_Ancient_Hebrew-PTNK ? Ancient_Hebrew
-UD_Arabic-NYUAD ar Arabic
+#UD_Arabic-NYUAD ar Arabic
 UD_Arabic-PADT ar Arabic *
 UD_Armenian-ArmTDP hy Armenian *
 UD_Armenian-BSUT hy Armenian

src/lambo/segmenter/lambo.py

@@ -68,7 +68,7 @@ class Lambo():
         return model_name
     
     @classmethod
-    def from_path(cls, model_path, model_name):
+    def from_path(cls, model_path, model_name, with_splitter = True):
         """
         Obtain a LAMBO segmenter by reading a model from a given path.
         
@@ -79,7 +79,7 @@ class Lambo():
         model = torch.load(model_path / (model_name + '.pth'), map_location=torch.device('cpu'))
         dict = Lambo.read_dict(model_path / (model_name + '.dict'))
         splitter=None
-        if (model_path / (model_name + '_subwords.pth')).exists():
+        if with_splitter and (model_path / (model_name + '_subwords.pth')).exists():
             from lambo.subwords.splitter import LamboSplitter
             splitter = LamboSplitter.from_path(model_path, model_name)
         return cls(model, dict, splitter)
@@ -229,7 +229,7 @@ class Lambo():
             if token_end:
                 # End of token
                 token = Token(turn_offset + token_begin, turn_offset + i + 1, text[token_begin:(i + 1)], mwtoken_end)
-                if mwtoken_end:
+                if mwtoken_end and self.splitter:
                     subwords=self.splitter.split(token.text)
                     if len(subwords)==1:
                         token.is_multi_word=False

src/lambo/utils/printer.py

@@ -48,11 +48,11 @@ def print_document_to_conll(document, path):
                     token_text = token_text_with_whitespace_for_conllu(token, document, turn, sentence).strip()
                     if token_text == '':
                         continue
-                    if token.is_multi_word and len(token.words) > 1:
+                    if token.is_multi_word and len(token.subwords) > 1:
                         file1.write(str(token_id))
-                        file1.write('-' + str(token_id + len(token.words) - 1))
+                        file1.write('-' + str(token_id + len(token.subwords) - 1))
                         file1.write('\t' + token_text + '\t_\t_\t_\t_\t_\t_\t_\t_\n')
-                        for word in token.words:
+                        for word in token.subwords:
                             file1.write(str(token_id) + '\t' + word + '\t_\t_\t_\t_\t' + str(token_id - 1) + '\t_\t_\t_\n')
                             token_id += 1
                     else: