modify file

ner-wikinews-dataset.py

@@ -1,100 +1,26 @@
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# 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: Address all TODOs and remove all explanatory comments
-"""TODO: Add a description here."""
-
-import csv
 import json
-import os
-import random
-from typing import Any, Dict, List
 
 import datasets
 
-# 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},
-author={huggingface, Inc.
-},
-year={2020}
-}
-"""
-
-# 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.
-"""
-
-# TODO: Add a link to an official homepage for the dataset here
-_HOMEPAGE = ""
-
-# TODO: Add the licence for the dataset here if you can find it
-_LICENSE = ""
-
-# TODO: Add link to the official dataset URLs here
-# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
-# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
+_CITATION = ""
+_DESCRIPTION = "This is a dataset of Wikinews articles manually labeled with the named entity label."
+_HOMEPAGE = "https://ja.wikinews.org/wiki/%E3%83%A1%E3%82%A4%E3%83%B3%E3%83%9A%E3%83%BC%E3%82%B8"
+_LICENSE = "This work is licensed under CC BY 2.5"
 _URL = "https://huggingface.co/datasets/llm-book/ner-wikinews-dataset/raw/main/annotated_wikinews.json"
 
 
-class NerWikinewsDatasetConfig(datasets.BuilderConfig):
-    """BuilderConfig for NerWikinewsDataset."""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for NerWikinewsDataset
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(NerWikinewsDatasetConfig, self).__init__(**kwargs)
-
-
-# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
 class NerWikinewsDataset(datasets.GeneratorBasedBuilder):
-    """TODO: Short description of my dataset."""
-
-    VERSION = datasets.Version("1.1.0")
-
-    # This is an example of a dataset with multiple configurations.
-    # If you don't want/need to define several sub-sets in your dataset,
-    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
-
-    # If you need to make complex sub-parts in the datasets with configurable options
-    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
-    # BUILDER_CONFIG_CLASS = MyBuilderConfig
-
-    # You will be able to load one or the other configurations in the following list with
-    # data = datasets.load_dataset('my_dataset', 'first_domain')
-    # data = datasets.load_dataset('my_dataset', 'second_domain')
-    # BUILDER_CONFIGS = [
-    #     datasets.BuilderConfig(
-    #         name="all",
-    #         version=VERSION,
-    #         description="This part of my dataset covers a first domain",
-    #     ),
-    # ]
-
-    # DEFAULT_CONFIG_NAME = "all"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="new-wikinews-dataset",
+            version=datasets.Version("1.1.0"),
+            description=_DESCRIPTION,
+        ),
+    ]
 
     def _info(self):
-        # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
         return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
             description=_DESCRIPTION,
-            # This defines the different columns of the dataset and their types
             features=datasets.Features(
                 {
                     "curid": datasets.Value("string"),
@@ -108,21 +34,16 @@ class NerWikinewsDataset(datasets.GeneratorBasedBuilder):
                             "type": datasets.Value(dtype="string"),
                         }
                     ],
-                    # These are the features of your dataset like images, labels ...
                 }
-            ),  # Here we define them above because they are different between the two configurations
-            # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
-            # specify them. They'll be used if as_supervised=True in builder.as_dataset.
-            # supervised_keys=("sentence", "label"),
-            # Homepage of the dataset for documentation
+            ),
             homepage=_HOMEPAGE,
-            # License for the dataset if available
             license=_LICENSE,
-            # Citation for the dataset
             citation=_CITATION,
         )
 
-    def _change_data_format(self, annotated_data: List[Dict[str, Any]]):
+    def _convert_data_format(
+        self, annotated_data: list[dict[str, any]]
+    ) -> list[dict[str, any]]:
         outputs = []
         for data in annotated_data:
             if data["annotations"] == []:
@@ -133,7 +54,10 @@ class NerWikinewsDataset(datasets.GeneratorBasedBuilder):
                     entities.append(
                         {
                             "name": result["value"]["text"],
-                            "span": [result["value"]["start"], result["value"]["end"]],
+                            "span": [
+                                result["value"]["start"],
+                                result["value"]["end"],
+                            ],
                             "type": result["value"]["labels"][0],
                         }
                     )
@@ -147,32 +71,20 @@ class NerWikinewsDataset(datasets.GeneratorBasedBuilder):
         return outputs
 
     def _split_generators(self, dl_manager):
-        # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
-        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
-
-        # 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
-        data_dir = dl_manager.download_and_extract(_URL)
-
-        # ダウンロードしたファイルを読み込み、全てのデータを取得
-
-        with open(data_dir, "r") as f:
-            test_data = json.load(f)
+        data_file = dl_manager.download_and_extract(_URL)
+        with open(data_file, "r") as f:
+            data = json.load(f)
 
-        test_data = self._change_data_format(test_data)
+        data = self._convert_data_format(data)
 
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
-                gen_kwargs={"data": test_data},
+                gen_kwargs={"data": data},
             ),
         ]
 
-    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
     def _generate_examples(self, data):
-        # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
-        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
         for key, data in enumerate(data):
             yield key, {
                 "curid": data["curid"],