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README.md

@@ -1,69 +1,84 @@
 ---
 dataset_info:
   features:
-  - name: text
-    dtype: string
-  - name: tokens
-    sequence: string
-  - name: tokens_offsets
-    sequence:
-      sequence: int32
-  - name: clinical_entity_tags
-    sequence:
-      class_label:
-        names:
-          '0': O
-          '1': B-CLINENTITY
-          '2': I-CLINENTITY
-  - name: temporal_information_tags
-    sequence:
-      class_label:
-        names:
-          '0': O
-          '1': B-EVENT
-          '2': B-ACTOR
-          '3': B-BODYPART
-          '4': B-TIMEX3
-          '5': B-RML
-          '6': I-EVENT
-          '7': I-ACTOR
-          '8': I-BODYPART
-          '9': I-TIMEX3
-          '10': I-RML
+    - name: text
+      dtype: string
+    - name: tokens
+      sequence: string
+    - name: tokens_offsets
+      sequence:
+        sequence: int32
+    - name: clinical_entity_tags
+      sequence:
+        class_label:
+          names:
+            "0": O
+            "1": B-CLINENTITY
+            "2": I-CLINENTITY
+    - name: temporal_information_tags
+      sequence:
+        class_label:
+          names:
+            "0": O
+            "1": B-EVENT
+            "2": B-ACTOR
+            "3": B-BODYPART
+            "4": B-TIMEX3
+            "5": B-RML
+            "6": I-EVENT
+            "7": I-ACTOR
+            "8": I-BODYPART
+            "9": I-TIMEX3
+            "10": I-RML
   config_name: e3c
   splits:
-  - name: en.layer1
-    num_bytes: 1273610
-    num_examples: 1520
-  - name: en.layer2
-    num_bytes: 2550153
-    num_examples: 2873
-  - name: es.layer1
-    num_bytes: 1252571
-    num_examples: 1134
-  - name: es.layer2
-    num_bytes: 2498266
-    num_examples: 2347
-  - name: eu.layer1
-    num_bytes: 1519021
-    num_examples: 3126
-  - name: eu.layer2
-    num_bytes: 839955
-    num_examples: 1594
-  - name: fr.layer1
-    num_bytes: 1258738
-    num_examples: 1109
-  - name: fr.layer2
-    num_bytes: 2628628
-    num_examples: 2389
-  - name: it.layer1
-    num_bytes: 1276534
-    num_examples: 1146
-  - name: it.layer2
-    num_bytes: 2641257
-    num_examples: 2436
+    - name: en.layer1
+      num_bytes: 1273610
+      num_examples: 1520
+    - name: en.layer2
+      num_bytes: 2550153
+      num_examples: 2873
+    - name: en.layer2.validation
+      num_bytes: 290108
+      num_examples: 334
+    - name: es.layer1
+      num_bytes: 1252571
+      num_examples: 1134
+    - name: es.layer2
+      num_bytes: 2498266
+      num_examples: 2347
+    - name: es.layer2.validation
+      num_bytes: 275770
+      num_examples: 261
+    - name: eu.layer1
+      num_bytes: 1519021
+      num_examples: 3126
+    - name: eu.layer2
+      num_bytes: 839955
+      num_examples: 1594
+    - name: eu.layer2.validation
+      num_bytes: 220097
+      num_examples: 468
+    - name: fr.layer1
+      num_bytes: 1258738
+      num_examples: 1109
+    - name: fr.layer2
+      num_bytes: 2628628
+      num_examples: 2389
+    - name: fr.layer2.validation
+      num_bytes: 282527
+      num_examples: 293
+    - name: it.layer1
+      num_bytes: 1276534
+      num_examples: 1146
+    - name: it.layer2
+      num_bytes: 2641257
+      num_examples: 2436
+    - name: it.layer2.validation
+      num_bytes: 286702
+      num_examples: 275
   download_size: 230213492
-  dataset_size: 17738733
+  dataset_size: 19093937
 ---
 
 # Dataset Card for E3C
@@ -92,4 +107,4 @@ information about clinical entities based on medical taxonomies, to be used for
     url = {https://uts.nlm.nih.gov/uts/umls/home},
     year = {2021},
 }
-```
+```

e3c.py

@@ -136,6 +136,17 @@ class E3C(datasets.GeneratorBasedBuilder):
                     ),
                 },
             ),
+            datasets.SplitGenerator(
+                name="en.layer2.validation",
+                gen_kwargs={
+                    "filepath": os.path.join(
+                        data_dir,
+                        "E3C-Corpus-2.0.0/data_validation",
+                        "English",
+                        "layer2",
+                    ),
+                },
+            ),
             datasets.SplitGenerator(
                 name="es.layer1",
                 gen_kwargs={
@@ -158,6 +169,17 @@ class E3C(datasets.GeneratorBasedBuilder):
                     ),
                 },
             ),
+            datasets.SplitGenerator(
+                name="es.layer2.validation",
+                gen_kwargs={
+                    "filepath": os.path.join(
+                        data_dir,
+                        "E3C-Corpus-2.0.0/data_validation",
+                        "Spanish",
+                        "layer2",
+                    ),
+                },
+            ),
             datasets.SplitGenerator(
                 name="eu.layer1",
                 gen_kwargs={
@@ -180,6 +202,17 @@ class E3C(datasets.GeneratorBasedBuilder):
                     ),
                 },
             ),
+            datasets.SplitGenerator(
+                name="eu.layer2.validation",
+                gen_kwargs={
+                    "filepath": os.path.join(
+                        data_dir,
+                        "E3C-Corpus-2.0.0/data_validation",
+                        "Basque",
+                        "layer2",
+                    ),
+                },
+            ),
             datasets.SplitGenerator(
                 name="fr.layer1",
                 gen_kwargs={
@@ -202,6 +235,17 @@ class E3C(datasets.GeneratorBasedBuilder):
                     ),
                 },
             ),
+            datasets.SplitGenerator(
+                name="fr.layer2.validation",
+                gen_kwargs={
+                    "filepath": os.path.join(
+                        data_dir,
+                        "E3C-Corpus-2.0.0/data_validation",
+                        "French",
+                        "layer2",
+                    ),
+                },
+            ),
             datasets.SplitGenerator(
                 name="it.layer1",
                 gen_kwargs={
@@ -224,6 +268,17 @@ class E3C(datasets.GeneratorBasedBuilder):
                     ),
                 },
             ),
+            datasets.SplitGenerator(
+                name="it.layer2.validation",
+                gen_kwargs={
+                    "filepath": os.path.join(
+                        data_dir,
+                        "E3C-Corpus-2.0.0/data_validation",
+                        "Italian",
+                        "layer2",
+                    ),
+                },
+            ),
         ]
 
     @staticmethod
@@ -289,8 +344,11 @@ class E3C(datasets.GeneratorBasedBuilder):
         for content in self.get_parsed_data(filepath):
             for sentence in content["SENTENCE"]:
                 tokens = [
-                    (token.offset + sentence[0], token.offset + sentence[0] + len(token.value),
-                     token.value)
+                    (
+                        token.offset + sentence[0],
+                        token.offset + sentence[0] + len(token.value),
+                        token.value,
+                    )
                     for token in list(tok.tokenize(sentence[-1]))
                 ]
 
@@ -335,7 +393,7 @@ class E3C(datasets.GeneratorBasedBuilder):
                                         temporal_information_labels[idx_token] = f"I-{entity_type}"
                 yield guid, {
                     "text": sentence[-1],
-                    "tokens": list(map(lambda tokens: tokens[2], filtered_tokens)),
+                    "tokens": list(map(lambda token: token[2], filtered_tokens)),
                     "clinical_entity_tags": clinical_labels,
                     "temporal_information_tags": temporal_information_labels,
                     "tokens_offsets": tokens_offsets,