Upload e3c.py

e3c.py

@@ -30,10 +30,10 @@ _URL = "https://github.com/hltfbk/E3C-Corpus/archive/refs/tags/v2.0.0.zip"
 
 
 class E3CConfig(datasets.BuilderConfig):
-    """BuilderConfig for NCBIDisease"""
+    """BuilderConfig for E3C."""
 
     def __init__(self, **kwargs):
-        """BuilderConfig for NCBIDisease.
+        """BuilderConfig for E3C.
         Args:
           **kwargs: keyword arguments forwarded to super.
         """
@@ -46,7 +46,7 @@ class E3C(datasets.GeneratorBasedBuilder):
         E3CConfig(
             name="e3c",
             version=VERSION,
-            description="this is the split of the layer 1 for English of E3C dataset",
+            description="this is an implementation of the E3C dataset",
         ),
     ]
 
@@ -54,7 +54,9 @@ class E3C(datasets.GeneratorBasedBuilder):
         """This method specifies the DatasetInfo which contains information and typings."""
         features = datasets.Features(
             {
+                "text": datasets.Value("string"),
                 "tokens": datasets.Sequence(datasets.Value("string")),
+                "tokens_offsets": datasets.Sequence(datasets.Sequence(datasets.Value("int32"))),
                 "ner_tags": datasets.Sequence(
                     datasets.features.ClassLabel(
                         names=[
@@ -263,8 +265,8 @@ class E3C(datasets.GeneratorBasedBuilder):
         Args:
             filepath: The path to the folder containing the files to parse.
         Yields:
-            The unique id of an example and the example itself containing tokens and ner_tags in
-            IOB format.
+            an example containing four fields: the text, the annotations, the tokens offsets and
+            the sentences.
         """
         guid = 0
         for content in self.get_parsed_data(filepath):
@@ -275,6 +277,9 @@ class E3C(datasets.GeneratorBasedBuilder):
                         content["TOKENS"],
                     )
                 )
+                tokens_offsets = [
+                    [token[0] - sentence[0], token[1] - sentence[0]] for token in filtered_tokens
+                ]
                 labels = ["O"] * len(filtered_tokens)
                 for entity_type in [
                     "CLINENTITY",
@@ -302,7 +307,9 @@ class E3C(datasets.GeneratorBasedBuilder):
                                 else:
                                     labels[idx_token] = f"{entity_type}"
                 yield guid, {
+                    "text": sentence[-1],
                     "tokens": list(map(lambda tokens: tokens[2], filtered_tokens)),
                     "ner_tags": labels,
+                    "tokens_offsets": tokens_offsets,
                 }
                 guid += 1