adding new zipped data files

.gitattributes

@@ -17,3 +17,5 @@
 data/dataset_dict.json filter=lfs diff=lfs merge=lfs -text
 data/test filter=lfs diff=lfs merge=lfs -text
 data/train filter=lfs diff=lfs merge=lfs -text
+data/test.zip filter=lfs diff=lfs merge=lfs -text
+data/train.zip filter=lfs diff=lfs merge=lfs -text

data/test.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eb7bab57150a9a64ad9a59e60f351bca97805199b9dbd322b37de3fcb4019f51
+size 30521828

data/train.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2c71f9c61dc301430c33856a12466f0fa1fcd2d0e58fa55467994e3841cac53d
+size 70366252

wikiner_fr.py

@@ -12,7 +12,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-"""TODO: Add a description here."""
+"""Wikiner dataset for NER in french language """
 
 from __future__ import absolute_import, division, print_function
 
@@ -23,25 +23,40 @@ import os
 import datasets
 
 
+
+_NER_LABEL_NAMES = [
+    "O",
+    "LOC",
+    "PER",
+    "MISC",
+    "ORG"
+]
+
+
+
 # TODO: Add BibTeX citation
 # Find for instance the citation on arxiv or on the dataset repo/website
 _CITATION = """\
 @InProceedings{huggingface:dataset,
-title = {A great new dataset},
-authors={huggingface, Inc.
-},
-year={2020}
+title = {Wikiner dataset for NER task in french},
+authors={Created by Nothman et al. at 2013},
+year={2013}
 }
 """
 
+
+
+
+
+
 # TODO: Add description of the dataset here
 # You can copy an official description
 _DESCRIPTION = """\
-This new dataset is designed to solve this great NLP task and is crafted with a lot of care. 
+Dataset can be used to train on NER task for french langugage.
 """
 
 # TODO: Add a link to an official homepage for the dataset here
-_HOMEPAGE = ""
+_HOMEPAGE = "https://www.sciencedirect.com/science/article/pii/S0004370212000276?via%3Dihub"
 
 # TODO: Add the licence for the dataset here if you can find it
 _LICENSE = ""
@@ -50,16 +65,14 @@ _LICENSE = ""
 # The HuggingFace dataset library don't host the datasets but only point to the original files
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
 _URLs = {
-    'first_domain': "https://huggingface.co/great-new-dataset-first_domain.zip",
-    'second_domain': "https://huggingface.co/great-new-dataset-second_domain.zip",
+#      "NER": "https://huggingface.co/datasets/Jean-Baptiste/wikiner_fr/tree/main/data"
 }
 
 
 # TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case
-class NewDataset(datasets.GeneratorBasedBuilder):
-    """TODO: Short description of my dataset."""
+class WikinerFr(datasets.GeneratorBasedBuilder):
 
-    VERSION = datasets.Version("1.1.0")
+    VERSION = datasets.Version("1.0.0")
 
     # This is an example of a dataset with multiple configurations.
     # If you don't want/need to define several sub-sets in your dataset,
@@ -73,32 +86,24 @@ class NewDataset(datasets.GeneratorBasedBuilder):
     # data = datasets.load_dataset('my_dataset', 'first_domain')
     # data = datasets.load_dataset('my_dataset', 'second_domain')
     BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="first_domain", version=VERSION, description="This part of my dataset covers a first domain"),
-        datasets.BuilderConfig(name="second_domain", version=VERSION, description="This part of my dataset covers a second domain"),
+        datasets.BuilderConfig(name="NER", version="0.0.1", description="Dataset for entity recognition")
     ]
 
-    DEFAULT_CONFIG_NAME = "first_domain"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+    DEFAULT_CONFIG_NAME = "NER"  # It's not mandatory to have a default configuration. Just use one if it make sense.
 
     def _info(self):
         # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
-        if self.config.name == "first_domain":  # This is the name of the configuration selected in BUILDER_CONFIGS above 
-            features = datasets.Features(
-                {
-                    "sentence": datasets.Value("string"),
-                    "option1": datasets.Value("string"),
-                    "answer": datasets.Value("string")
-                    # These are the features of your dataset like images, labels ...
-                }
-            )
-        else:  # This is an example to show how to have different features for "first_domain" and "second_domain"
+        if self.config.name == "NER":  # This is the name of the configuration selected in BUILDER_CONFIGS above 
             features = datasets.Features(
                 {
-                    "sentence": datasets.Value("string"),
-                    "option2": datasets.Value("string"),
-                    "second_domain_answer": datasets.Value("string")
-                    # These are the features of your dataset like images, labels ...
+                    "id": datasets.Sequence(feature=datasets.Value("int32")),
+                    "ner_tags": datasets.Sequence(
+                        feature=datasets.ClassLabel(num_classes=len(_NER_LABEL_NAMES), names=_NER_LABEL_NAMES)
+                    ),
+                    "tokens": datasets.Sequence(feature=datasets.Value("string")),
                 }
             )
+
         return datasets.DatasetInfo(
             # This is the description that will appear on the datasets page.
             description=_DESCRIPTION,
@@ -107,7 +112,7 @@ class NewDataset(datasets.GeneratorBasedBuilder):
             # If there's a common (input, target) tuple from the features,
             # specify them here. They'll be used if as_supervised=True in
             # builder.as_dataset.
-            supervised_keys=None,
+            supervised_keys=("id", "ner_tags"),
             # Homepage of the dataset for documentation
             homepage=_HOMEPAGE,
             # License for the dataset if available
@@ -124,14 +129,20 @@ class NewDataset(datasets.GeneratorBasedBuilder):
         # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs
         # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
         # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive 
-        my_urls = _URLs[self.config.name]
-        data_dir = dl_manager.download_and_extract(my_urls)
+        
+        if self.config.data_dir:
+            data_dir = self.config.data_dir
+        else:
+            my_urls = _URLs[self.config.name]
+            data_dir = dl_manager.download_and_extract(my_urls)
+
+
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filepath": os.path.join(data_dir, "train.jsonl"),
+                    "filepath": os.path.join(data_dir, "train.zip"),
                     "split": "train",
                 },
             ),
@@ -139,18 +150,10 @@ class NewDataset(datasets.GeneratorBasedBuilder):
                 name=datasets.Split.TEST,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filepath": os.path.join(data_dir, "test.jsonl"),
+                    "filepath": os.path.join(data_dir, "test.zip"),
                     "split": "test"
                 },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(data_dir, "dev.jsonl"),
-                    "split": "dev",
-                },
-            ),
+            )
         ]
 
     def _generate_examples(
@@ -159,19 +162,13 @@ class NewDataset(datasets.GeneratorBasedBuilder):
         """ Yields examples as (key, example) tuples. """
         # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
         # The `key` is here for legacy reason (tfds) and is not important in itself.
-
-        with open(filepath, encoding="utf-8") as f:
-            for id_, row in enumerate(f):
-                data = json.loads(row)
-                if self.config.name == "first_domain":
-                    yield id_, {
-                        "sentence": data["sentence"],
-                        "option1": data["option1"],
-                        "answer": "" if split == "test" else data["answer"],
-                    }
-                else:
-                    yield id_, {
-                        "sentence": data["sentence"],
-                        "option2": data["option2"],
-                        "second_domain_answer": "" if split == "test" else data["second_domain_answer"],
-                    }
+        print(filepath)
+#         with open(filepath, encoding="utf-8") as f:
+#             for id_, row in enumerate(f):
+#                 data = json.loads(row)
+#                 if self.config.name == "NER":
+#                     yield id_, {
+#                         "sentence": data["sentence"],
+#                         "option1": data["option1"],
+#                         "answer": "" if split == "test" else data["answer"],
+#                     }