init

README.md

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+---
+language:
+- en
+license:
+- other
+multilinguality:
+- monolingual
+size_categories:
+- 1k<10K
+task_categories:
+- token-classification
+task_ids:
+- named-entity-recognition
+pretty_name: TweetNER7
+---
+
+# Dataset Card for "tner/tweetner7"
+
+## Dataset Description
+
+- **Repository:** [T-NER](https://github.com/asahi417/tner)
+- **Paper:** TBA
+- **Dataset:** TweetNER7
+- **Domain:** Twitter
+- **Number of Entity:** 7
+
+
+### Dataset Summary
+TweeBank NER dataset formatted in a part of [TNER](https://github.com/asahi417/tner) project.
+- Entity Types: `corperation`, `creative_work`, `event`, `group`, `location`, `product`, `person` 
+
+## Dataset Structure
+
+### Data Instances
+An example of `train` looks as follows.
+
+```
+{
+  
+}
+```
+
+### Label ID
+The label2id dictionary can be found at [here](https://huggingface.co/datasets/tner/tweetner7/raw/main/dataset/label.json).
+```python
+{
+    "B-corporation": 0,
+    "B-creative_work": 1,
+    "B-event": 2,
+    "B-group": 3,
+    "B-location": 4,
+    "B-person": 5,
+    "B-product": 6,
+    "I-corporation": 7,
+    "I-creative_work": 8,
+    "I-event": 9,
+    "I-group": 10,
+    "I-location": 11,
+    "I-person": 12,
+    "I-product": 13,
+    "O": 14
+}
+```
+
+### Data Splits
+
+|  name   |train|validation|test|
+|---------|----:|---------:|---:|
+|tweetner7 | 1639|      710 |1201|
+
+### Citation Information
+
+```
+TBA
+```

dataset/label.json

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+{"B-corporation": 0, "B-creative_work": 1, "B-event": 2, "B-group": 3, "B-location": 4, "B-person": 5, "B-product": 6, "I-corporation": 7, "I-creative_work": 8, "I-event": 9, "I-group": 10, "I-location": 11, "I-person": 12, "I-product": 13, "O": 14}

tweetner7.py

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+""" NER dataset compiled by T-NER library https://github.com/asahi417/tner/tree/master/tner """
+import json
+from itertools import chain
+import datasets
+
+logger = datasets.logging.get_logger(__name__)
+_DESCRIPTION = """[TweetNER7](TBA)"""
+_NAME = "tweetner7"
+_VERSION = "1.0.0"
+_CITATION = """
+TBA
+"""
+
+_HOME_PAGE = "https://github.com/asahi417/tner"
+_URL = f'https://huggingface.co/datasets/tner/{_NAME}/raw/main/dataset'
+_URLS = {
+    str(datasets.Split.TEST): [f'{_URL}/2021.test.json'],
+    str(datasets.Split.VALIDATION): [f'{_URL}/2020.dev.json'],
+    str(datasets.Split.TRAIN): [f'{_URL}/2020.train.json'],
+    f'{str(datasets.Split.TEST)}_2020': [f'{_URL}/2020.test.json'],
+    f'{str(datasets.Split.TEST)}_2021': [f'{_URL}/2021.test.json'],
+    f'{str(datasets.Split.VALIDATION)}_2020': [f'{_URL}/2020.dev.json'],
+    f'{str(datasets.Split.VALIDATION)}_2021': [f'{_URL}/2021.dev.json'],
+    f'{str(datasets.Split.TRAIN)}_2020': [f'{_URL}/2020.train.json'],
+    f'{str(datasets.Split.TRAIN)}_2021': [f'{_URL}/2021.train.json'],
+    f'{str(datasets.Split.VALIDATION)}_random': [f'{_URL}/random.dev.json'],
+    f'{str(datasets.Split.TRAIN)}_random': [f'{_URL}/random.train.json'],
+    f'extra_2020': [f'{_URL}/extra/2020.extra{i:02d}.json' for i in range(9)],
+    f'extra_2021': [f'{_URL}/extra/2021.extra{i:02d}.json' for i in range(10)]
+}
+
+
+class TweetNER7Config(datasets.BuilderConfig):
+    """BuilderConfig"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(TweetNER7Config, self).__init__(**kwargs)
+
+
+class TweetNER7(datasets.GeneratorBasedBuilder):
+    """Dataset."""
+
+    BUILDER_CONFIGS = [
+        TweebankNERConfig(name=_NAME, version=datasets.Version(_VERSION), description=_DESCRIPTION),
+    ]
+
+    def _split_generators(self, dl_manager):
+        downloaded_file = dl_manager.download_and_extract(_URLS)
+        return [datasets.SplitGenerator(name=i, gen_kwargs={"filepaths": downloaded_file[str(i)]})
+                for i in [datasets.Split.TRAIN, datasets.Split.VALIDATION, datasets.Split.TEST]]
+
+    def _generate_examples(self, filepaths):
+        _key = 0
+        for filepath in filepaths:
+            logger.info(f"generating examples from = {filepath}")
+            with open(filepath, encoding="utf-8") as f:
+                _list = [i for i in f.read().split('\n') if len(i) > 0]
+                for i in _list:
+                    data = json.loads(i)
+                    yield _key, data
+                    _key += 1
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "tags": datasets.Sequence(datasets.Value("int32")),
+                    "id": datasets.Value("string"),
+                    "date": datasets.Value("string")
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOME_PAGE,
+            citation=_CITATION,
+        )