Datasets:

EMBO
/

sd-character-level-ner

Tasks:

Text Classification

Modalities:

Sub-tasks:

multi-class-classification

named-entity-recognition

Languages:

Size:

Libraries:

License:

Dataset card Viewer Files Files and versions Community

drAbreu commited on Sep 22, 2022

Commit

ffafe20

•

1 Parent(s): 01579ca

Update sd-character-level-ner.py

Files changed (1) hide show

sd-character-level-ner.py +4 -6

sd-character-level-ner.py CHANGED Viewed

@@ -83,23 +83,21 @@ class SourceDataNLP(datasets.GeneratorBasedBuilder):
         if self.config.name == "NER":
             features = datasets.Features(
                 {
-                    "words": datasets.Sequence(feature=datasets.Value("string")),
                     "labels": datasets.Sequence(
                         feature=datasets.ClassLabel(num_classes=len(self._NER_LABEL_NAMES),
                                                     names=self._NER_LABEL_NAMES)
-                    ),
-                    "tag_mask": datasets.Sequence(feature=datasets.Value("int8")),
                 }
             )
         elif self.config.name == "PANELIZATION":
             features = datasets.Features(
                 {
-                    "words": datasets.Sequence(feature=datasets.Value("string")),
                     "labels": datasets.Sequence(
                         feature=datasets.ClassLabel(num_classes=len(self._PANEL_START_NAMES),
                                                     names=self._PANEL_START_NAMES)
-                    ),
-                    "tag_mask": datasets.Sequence(feature=datasets.Value("int8")),
                 }
             )

         if self.config.name == "NER":
             features = datasets.Features(
                 {
+                    "text": datasets.Value("string"),
                     "labels": datasets.Sequence(
                         feature=datasets.ClassLabel(num_classes=len(self._NER_LABEL_NAMES),
                                                     names=self._NER_LABEL_NAMES)
+                    )
                 }
             )
         elif self.config.name == "PANELIZATION":
             features = datasets.Features(
                 {
+                    "text": datasets.Value("string"),
                     "labels": datasets.Sequence(
                         feature=datasets.ClassLabel(num_classes=len(self._PANEL_START_NAMES),
                                                     names=self._PANEL_START_NAMES)
+                    )
                 }
             )