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.ipynb_checkpoints/README-checkpoint.md

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+---
+annotations_creators:
+- machine-translated
+language_creators:
+- machine-translated
+language:
+- zh
+license:
+- cc-by-sa-4.0
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- squad_v2
+task_categories:
+- question-answering
+task_ids:
+- open-domain-qa
+- extractive-qa
+pretty_name: Chinese SQuAD 2.0
+---
+
+# Dataset Card for Chinese SQuAD 2.0
+
+## Dataset Description
+
+### Dataset Summary
+
+This is a Chinese translation of the SQuAD 2.0 dataset, translated from the original English version. Like SQuAD 2.0, it contains both answerable and unanswerable questions. The dataset is designed for Chinese reading comprehension and question answering tasks.
+
+Source: [ChineseSquad](https://github.com/junzeng-pluto/ChineseSquad)
+
+### Dataset Structure
+
+The dataset is stored in Parquet format and contains the following fields:
+
+```python
+{
+    'id': string,
+    'title': string,
+    'context': string,
+    'question': string,
+    'answers': {
+        'text': List[string],
+        'answer_start': List[int]
+    }
+}
+```
+
+### Data Splits
+
+| Split      | Total Examples | Answerable | Unanswerable |
+|------------|---------------|------------|--------------|
+| train      | 90,027        | 46,529     | 43,498       |
+| validation | 9,936         | 3,991      | 5,945        |
+
+### Usage
+
+```python
+from datasets import load_dataset
+
+# Load from Hugging Face Hub
+dataset = load_dataset("real-jiakai/chinese-squad-v2")
+
+# Example usage
+example = dataset['train'][0]
+print(f"Question: {example['question']}")
+print(f"Context: {example['context']}")
+print(f"Answer: {example['answers']['text']}")
+```
+
+Example output:
+```python
+{
+    'id': '56be85543aeaaa14008c9065',
+    'title': '碧昂斯',
+    'context': '碧昂丝·吉赛尔·诺尔斯·卡特（生于1981年9月4日）是美国歌手、作曲家、唱片制作人和女演员。...',
+    'question': '碧昂丝在成长过程中，在哪些领域竞争？',
+    'answers': {
+        'text': ['歌舞'],
+        'answer_start': [70]
+    }
+}
+```
+
+### Citation
+
+If you use this dataset, please cite both the original SQuAD 2.0 paper and the Chinese translation:
+
+```bibtex
+@inproceedings{rajpurkar-etal-2018-know,
+    title = "Know What You Don't Know: Unanswerable Questions for {SQ}u{AD}",
+    author = "Rajpurkar, Pranav and Jia, Robin and Liang, Percy",
+    booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics",
+    year = "2018",
+    pages = "784--789",
+}
+
+@misc{chinese-squad,
+    title = "ChineseSquad: A Chinese Translation of SQuAD 2.0",
+    author = "Zeng, Jun",
+    url = "https://github.com/junzeng-pluto/ChineseSquad",
+}
+```
+
+### License
+
+This dataset is licensed under CC BY-SA 4.0, following the original SQuAD 2.0 license.
+
+### Limitations and Bias
+
+- Current version contains ~100k examples, which is less than the original SQuAD 2.0
+- As a machine-translated dataset, some nuances from the original English text might be lost or altered
+- The answer spans are machine-aligned after translation, which might introduce some noise
+- The dataset inherits any biases present in the original SQuAD 2.0 dataset
+- Translation quality may vary across different examples

.ipynb_checkpoints/dataset_info-checkpoint.json

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+{
+    "config_name": "chinese_squadv2",
+    "features": {
+        "id": {"dtype": "string", "_type": "Value"},
+        "title": {"dtype": "string", "_type": "Value"},
+        "context": {"dtype": "string", "_type": "Value"},
+        "question": {"dtype": "string", "_type": "Value"},
+        "answers": {
+            "feature": {
+                "text": {"dtype": "string", "_type": "Sequence"},
+                "answer_start": {"dtype": "int32", "_type": "Sequence"}
+            },
+            "_type": "Struct"
+        }
+    },
+    "splits": {
+        "train": {
+            "num_examples": 90027
+        },
+        "validation": {
+            "num_examples": 9936
+        }
+    }
+}

README.md

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+---
+annotations_creators:
+- machine-translated
+language_creators:
+- machine-translated
+language:
+- zh
+license:
+- cc-by-sa-4.0
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- squad_v2
+task_categories:
+- question-answering
+task_ids:
+- open-domain-qa
+- extractive-qa
+pretty_name: Chinese SQuAD 2.0
+---
+
+# Dataset Card for Chinese SQuAD 2.0
+
+## Dataset Description
+
+### Dataset Summary
+
+This is a Chinese translation of the SQuAD 2.0 dataset, translated from the original English version. Like SQuAD 2.0, it contains both answerable and unanswerable questions. The dataset is designed for Chinese reading comprehension and question answering tasks.
+
+Source: [ChineseSquad](https://github.com/junzeng-pluto/ChineseSquad)
+
+### Dataset Structure
+
+The dataset is stored in Parquet format and contains the following fields:
+
+```python
+{
+    'id': string,
+    'title': string,
+    'context': string,
+    'question': string,
+    'answers': {
+        'text': List[string],
+        'answer_start': List[int]
+    }
+}
+```
+
+### Data Splits
+
+| Split      | Total Examples | Answerable | Unanswerable |
+|------------|---------------|------------|--------------|
+| train      | 90,027        | 46,529     | 43,498       |
+| validation | 9,936         | 3,991      | 5,945        |
+
+### Usage
+
+```python
+from datasets import load_dataset
+
+# Load from Hugging Face Hub
+dataset = load_dataset("real-jiakai/chinese-squad-v2")
+
+# Example usage
+example = dataset['train'][0]
+print(f"Question: {example['question']}")
+print(f"Context: {example['context']}")
+print(f"Answer: {example['answers']['text']}")
+```
+
+Example output:
+```python
+{
+    'id': '56be85543aeaaa14008c9065',
+    'title': '碧昂斯',
+    'context': '碧昂丝·吉赛尔·诺尔斯·卡特（生于1981年9月4日）是美国歌手、作曲家、唱片制作人和女演员。...',
+    'question': '碧昂丝在成长过程中，在哪些领域竞争？',
+    'answers': {
+        'text': ['歌舞'],
+        'answer_start': [70]
+    }
+}
+```
+
+### Citation
+
+If you use this dataset, please cite both the original SQuAD 2.0 paper and the Chinese translation:
+
+```bibtex
+@inproceedings{rajpurkar-etal-2018-know,
+    title = "Know What You Don't Know: Unanswerable Questions for {SQ}u{AD}",
+    author = "Rajpurkar, Pranav and Jia, Robin and Liang, Percy",
+    booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics",
+    year = "2018",
+    pages = "784--789",
+}
+
+@misc{chinese-squad,
+    title = "ChineseSquad: A Chinese Translation of SQuAD 2.0",
+    author = "Zeng, Jun",
+    url = "https://github.com/junzeng-pluto/ChineseSquad",
+}
+```
+
+### License
+
+This dataset is licensed under CC BY-SA 4.0, following the original SQuAD 2.0 license.
+
+### Limitations and Bias
+
+- Current version contains ~100k examples, which is less than the original SQuAD 2.0
+- As a machine-translated dataset, some nuances from the original English text might be lost or altered
+- The answer spans are machine-aligned after translation, which might introduce some noise
+- The dataset inherits any biases present in the original SQuAD 2.0 dataset
+- Translation quality may vary across different examples

data/train-00000-of-00001.parquet

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+size 14874843

data/validation-00000-of-00001.parquet

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+oid sha256:49bcdd1c3673665edc530571db8b5156921760fe1646e0e354c5c6683a6703d7
+size 971092

dataset_info.json

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+{
+    "config_name": "chinese_squadv2",
+    "features": {
+        "id": {"dtype": "string", "_type": "Value"},
+        "title": {"dtype": "string", "_type": "Value"},
+        "context": {"dtype": "string", "_type": "Value"},
+        "question": {"dtype": "string", "_type": "Value"},
+        "answers": {
+            "feature": {
+                "text": {"dtype": "string", "_type": "Sequence"},
+                "answer_start": {"dtype": "int32", "_type": "Sequence"}
+            },
+            "_type": "Struct"
+        }
+    },
+    "splits": {
+        "train": {
+            "num_examples": 90027
+        },
+        "validation": {
+            "num_examples": 9936
+        }
+    }
+}