Update sd-nlp-non-tokenized.py

sd-nlp-non-tokenized.py

@@ -49,7 +49,7 @@ class SourceDataNLP(datasets.GeneratorBasedBuilder):
     _SEMANTIC_SMALL_MOL_ROLES_LABEL_NAMES = ["O", "B-CONTROLLED_VAR", "I-CONTROLLED_VAR", "B-MEASURED_VAR", "I-MEASURED_VAR"]
     _BORING_LABEL_NAMES = ["O", "B-BORING", "I-BORING"]
     _PANEL_START_NAMES = ["O", "B-PANEL_START", "I-PANEL_START"]
-    _ROLES_NAMES = ["O", "CONTROLLED_VAR", "MEASURED_VAR"]
+    _ROLES_NAMES = ["O", "B-CONTROLLED_VAR", "B-MEASURED_VAR"]
 
     _CITATION = """\
     @Unpublished{
@@ -157,6 +157,7 @@ class SourceDataNLP(datasets.GeneratorBasedBuilder):
                         feature=datasets.ClassLabel(num_classes=len(self._ROLES_NAMES),
                                                     names=self._ROLES_NAMES)
                     ),
+                    "tag_mask": datasets.Sequence(feature=datasets.Value("int8")),
                 }
             )
 
@@ -243,8 +244,9 @@ class SourceDataNLP(datasets.GeneratorBasedBuilder):
                     yield id_, {"words": data["words"],
                                 "labels": data["label_ids"]["boring"]}
                 elif self.config.name == "ROLES":
-                    yield id_, {"words": data["text_generic_roles"],
-                                "labels": data["labels_generic_roles"]}
+                    yield id_, {"words": data["generic_roles"]["words"],
+                                "labels": data["generic_roles"]["roles"],
+                               "tag_mask": data["generic_roles"]["tag_mask"]}
                 elif self.config.name == "PANELIZATION":
                     labels = data["label_ids"]["panel_start"]
                     tag_mask = [1 if t == "B-PANEL_START" else 0 for t in labels]