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.ipynb_checkpoints/EMEA-checkpoint.py

@@ -0,0 +1,58 @@
+import os
+import datasets
+
+class MyDatasetConfig(datasets.BuilderConfig):
+    """Builder config for original vs processed."""
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+class MyDataset(datasets.GeneratorBasedBuilder):
+
+    BUILDER_CONFIGS = [
+        MyDatasetConfig(
+            name="original",
+            version=datasets.Version("1.0.0"),
+            description="Original dataset",
+        ),
+        MyDatasetConfig(
+            name="processed",
+            version=datasets.Version("1.0.0"),
+            description="Processed dataset",
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo()  # features inferred automatically from Parquet
+
+    def _split_generators(self, dl_manager):
+    
+        data_dir = self.config.name + "_data"
+    
+        data_files = {
+            "train": os.path.join(data_dir, "train-00000-of-00001.parquet"),
+            "validation": os.path.join(data_dir, "validation-00000-of-00001.parquet"),
+            "test": os.path.join(data_dir, "test-00000-of-00001.parquet"),
+        }
+    
+        downloaded_files = dl_manager.download(data_files)
+    
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": downloaded_files["train"]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": downloaded_files["validation"]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": downloaded_files["test"]},
+            ),
+        ]
+    
+    def _generate_examples(self, filepath):
+        import pyarrow.parquet as pq
+        table = pq.read_table(filepath)
+        for i in range(table.num_rows):
+            yield i, table.slice(i, 1).to_pydict()

EMEA.py

@@ -0,0 +1,58 @@
+import os
+import datasets
+
+class MyDatasetConfig(datasets.BuilderConfig):
+    """Builder config for original vs processed."""
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+class MyDataset(datasets.GeneratorBasedBuilder):
+
+    BUILDER_CONFIGS = [
+        MyDatasetConfig(
+            name="original",
+            version=datasets.Version("1.0.0"),
+            description="Original dataset",
+        ),
+        MyDatasetConfig(
+            name="processed",
+            version=datasets.Version("1.0.0"),
+            description="Processed dataset",
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo()  # features inferred automatically from Parquet
+
+    def _split_generators(self, dl_manager):
+    
+        data_dir = self.config.name + "_data"
+    
+        data_files = {
+            "train": os.path.join(data_dir, "train-00000-of-00001.parquet"),
+            "validation": os.path.join(data_dir, "validation-00000-of-00001.parquet"),
+            "test": os.path.join(data_dir, "test-00000-of-00001.parquet"),
+        }
+    
+        downloaded_files = dl_manager.download(data_files)
+    
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": downloaded_files["train"]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": downloaded_files["validation"]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": downloaded_files["test"]},
+            ),
+        ]
+    
+    def _generate_examples(self, filepath):
+        import pyarrow.parquet as pq
+        table = pq.read_table(filepath)
+        for i in range(table.num_rows):
+            yield i, table.slice(i, 1).to_pydict()

README.md

@@ -1,3 +1,59 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: original_data/train-*
+  - split: validation
+    path: original_data/validation-*
+  - split: test
+    path: original_data/test-*
+task_categories:
+- text-classification
+- text-generation
+- zero-shot-classification
+- token-classification
+language:
+- fr
+tags:
+- UMLS
+- entity_linking
+- biomedical
+size_categories:
+- 1K<n<10K
+dataset_info:
+  features:
+  - name: id
+    dtype: string
+  - name: document_id
+    dtype: string
+  - name: entities
+    list:
+    - name: id
+      dtype: string
+    - name: normalized
+      list:
+      - name: db_id
+        dtype: string
+      - name: db_name
+        dtype: string
+    - name: offsets
+      sequence:
+        sequence: int64
+    - name: text
+      sequence: string
+    - name: type
+      dtype: string
+  - name: passages
+    list:
+    - name: id
+      dtype: string
+    - name: offsets
+      sequence:
+        sequence: int64
+    - name: text
+      sequence: string
+    - name: type
+      dtype: string
+---

original_data/test-00000-of-00001.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:edc995c4f6fcf164dabdae65d40e57131e13026d2f7c54d8499a8fb480c6ca00
+size 82297

original_data/train-00000-of-00001.parquet

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+oid sha256:bec64ac095eb3fbc03a176ab8cfdaa18b4279aaf77aeceea5657d21b9df9e59b
+size 112647

original_data/validation-00000-of-00001.parquet

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+oid sha256:9b14078d3b7d5841430f32cfcd6a8dd89e839016261fee6996a83949d9a0ab90
+size 93576

processed_data/test-00000-of-00001.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:835de8984ce3671574f60f6564fe23668e6fee8627cd734b2f12121e6115c329
+size 81212

processed_data/train-00000-of-00001.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ce3f6fdff68245dc8155fd7366a610325a3b5f8a26b96b859b500b3a1f4ed398
+size 111266

processed_data/validation-00000-of-00001.parquet

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+oid sha256:3d6e02f75376dd604f5afbd60810013ab6f4234a0608aa3d47363b8fb1af5329
+size 91948