Update files from the datasets library (from 1.4.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.4.0

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README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- found
+languages:
+- th
+licenses:
+- mit
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K
+source_datasets:
+- extended|other-iapp-wiki-qa-dataset
+task_categories:
+- question-answering
+task_ids:
+- extractive-qa
+- open-domain-qa
+---
+
+# Dataset Card for `iapp_wiki_qa_squad`
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** https://github.com/iapp-technology/iapp-wiki-qa-dataset
+- **Repository:** https://github.com/iapp-technology/iapp-wiki-qa-dataset
+- **Paper:**
+- **Leaderboard:**
+- **Point of Contact:** https://github.com/iapp-technology/iapp-wiki-qa-dataset
+
+### Dataset Summary
+
+`iapp_wiki_qa_squad` is an extractive question answering dataset from Thai Wikipedia articles. It is adapted from [the original iapp-wiki-qa-dataset](https://github.com/iapp-technology/iapp-wiki-qa-dataset) to [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format, resulting in 5761/742/739 questions from 1529/191/192 articles.
+
+### Supported Tasks and Leaderboards
+
+extractive question answering
+
+### Languages
+
+Thai
+
+## Dataset Structure
+
+### Data Instances
+
+An example from the dataset:
+```
+{'article_id': '0U2lA8nJQESIxbZrjZQc',
+'question_id': '0U2lA8nJQESIxbZrjZQc_000',
+'context': 'นายสุวัฒน์ วรรณศิริกุล (1 พฤศจิกายน พ.ศ. 2476 - 31 กรกฎาคม พ.ศ. 2555) อดีตรองหัวหน้าพรรคพลังประชาชน อดีตประธานสมาชิกสภาผู้แทนราษฎร และประธานภาคกรุงเทพมหานคร พรรคพลังประชาชน อดีตสมาชิกสภาผู้แทนราษฎรกรุงเทพมหานครหลายสมัย ได้รับการเลือกตั้งเป็นสมาชิกสภาผู้แทนราษฎรครั้งแรกในปี พ.ศ. 2529 ในสังกัดพรรคประชากรไทย และสังกัดพรรคพลังประชาชน เป็นพรรคสุดท้าย',
+'question': 'สุวัฒน์ วรรณศิริกุล เกิดวันที่เท่าไร',
+'answers': {'text': ['1 พฤศจิกายน พ.ศ. 2476'],
+ 'answer_start': [24],
+ 'answer_end': [45]},
+'title': 'สุวัฒน์ วรรณศิริกุล',
+'created_by': 'gmnjGRF0y0g7QRZDd9Qgz3AgiHJ3',
+'created_on': '2019-08-18 05:05:51.358000+00:00',
+'is_pay': {'date': None, 'status': False}}
+{'article_id': '01KZTrxgvC5mOovXFMPJ',
+'question_id': '01KZTrxgvC5mOovXFMPJ_000',
+'context': 'พัทธ์ธีรา ศรุติพงศ์โภคิน (เกิด 3 ธันวาคม พ.ศ. 2533) หรือชื่อเล่นว่า อร เป็นนักแสดงหญิงชาวไทย สำเร็จมัธยมศึกษาจากCatholic Cathedral College ประเทศนิวซีแลนด์ และปริญญาตรีจากRaffles International College สาขา Business Marketing\n\nเข้าสู่วงการตั้งแต่อายุ 6 ขวบ จากการแสดงละครเวทีกับ ครูชลประคัลภ์ จันทร์เรือง จากนั้นก็เล่นโฆษณาในวัยเด็ก 2- 3 ชิ้น และยังเคยแสดงช่วงละครสั้น ในรายการซุปเปอร์จิ๋ว ประมาณปี 2542\n\nปัจจุบันเป็นทั้ง นักแสดง , พิธีกร และ วีเจ อยู่ที่คลื่น เก็ท 102.5 Bangkok International Hits Music Station และยังเป็นพิธีกรให้กับช่อง ทรู มิวสิก',
+'question': 'พัทธ์ธีรา ศรุติพงศ์โภคิน เกิดวันที่เท่าไร',
+'answers': {'text': ['3 ธันวาคม พ.ศ. 2533'],
+ 'answer_start': [31],
+ 'answer_end': [50]},
+'title': 'พัทธ์ธีรา ศรุติพงศ์โภคิน',
+'created_by': 'gmnjGRF0y0g7QRZDd9Qgz3AgiHJ3',
+'created_on': '2019-08-07 14:00:38.778000+00:00',
+'is_pay': {'status': True,
+ 'total': 2.5,
+ 'date': '2019-08-13 10:47:28.095000+00:00'}}
+```
+
+### Data Fields
+
+```
+{
+    "question_id": question id
+    "article_id": article id
+    "title": article title
+    "context": article texts
+    "question": question
+    "answers":
+        {
+            "text": answer text
+            "answer_start": answer beginning position
+            "answer_end": answer exclusive upper bound position
+        }
+    ),
+}
+```
+
+### Data Splits
+
+|             | train | valid | test |
+|-------------|-------|-------|------|
+| # questions | 5761  | 742   | 739  |
+| # articles  | 1529  | 191   | 192  |
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+From the original `iapp-wiki-qa-dataset`, [@cstorm125](https://github.com/cstorm125/) applied the following processing:
+
+- Select questions with one, non-empty answer
+- Select questions whose answers match `textDetection` fields
+- Select questions whose answers are 100-character long or shorter
+- 80/10/10 train-validation-split at article level
+
+#### Who are the source language producers?
+
+Wikipedia authors for contexts and annotators hired by [iApp](https://iapp.co.th/) for questions and answer annotations
+
+### Annotations
+
+#### Annotation process
+
+Annotators hired by [iApp](https://iapp.co.th/) are asked create questions and answers for each article.
+
+#### Who are the annotators?
+
+Annotators hired by [iApp](https://iapp.co.th/)
+
+### Personal and Sensitive Information
+
+All contents are from Wikipedia. No personal and sensitive information is expected to be included.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+- open-domain, extractive question answering in Thai
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+Original dataset by [iApp](https://iapp.co.th/). SQuAD formattting by [PyThaiNLP](https://github.com/PyThaiNLP/).
+
+### Licensing Information
+
+MIT
+
+### Citation Information
+
+```
+@dataset{kobkrit_viriyayudhakorn_2021_4539916,
+  author       = {Kobkrit Viriyayudhakorn and
+                  Charin Polpanumas},
+  title        = {iapp\_wiki\_qa\_squad},
+  month        = feb,
+  year         = 2021,
+  publisher    = {Zenodo},
+  version      = 1,
+  doi          = {10.5281/zenodo.4539916},
+  url          = {https://doi.org/10.5281/zenodo.4539916}
+}
+```
+
+### Contributions
+
+Thanks to [@cstorm125](https://github.com/cstorm125) for adding this dataset.

dataset_infos.json

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+{"iapp_wiki_qa_squad": {"description": "`iapp_wiki_qa_squad` is an extractive question answering dataset from Thai Wikipedia articles.\nIt is adapted from [the original iapp-wiki-qa-dataset](https://github.com/iapp-technology/iapp-wiki-qa-dataset)\nto [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format, resulting in\n5761/742/739 questions from 1529/191/192 articles.\n", "citation": "@dataset{kobkrit_viriyayudhakorn_2021_4539916,\n  author       = {Kobkrit Viriyayudhakorn and\n                  Charin Polpanumas},\n  title        = {iapp\\_wiki\\_qa\\_squad},\n  month        = feb,\n  year         = 2021,\n  publisher    = {Zenodo},\n  version      = 1,\n  doi          = {10.5281/zenodo.4539916},\n  url          = {https://doi.org/10.5281/zenodo.4539916}\n}\n", "homepage": "https://github.com/iapp-technology/iapp-wiki-qa-dataset/", "license": "", "features": {"question_id": {"dtype": "string", "id": null, "_type": "Value"}, "article_id": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "answers": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "answer_start": {"dtype": "int32", "id": null, "_type": "Value"}, "answer_end": {"dtype": "int32", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "iapp_wiki_qa_squad", "config_name": "iapp_wiki_qa_squad", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 16107541, "num_examples": 5761, "dataset_name": "iapp_wiki_qa_squad"}, "validation": {"name": "validation", "num_bytes": 2120768, "num_examples": 742, "dataset_name": "iapp_wiki_qa_squad"}, "test": {"name": "test", "num_bytes": 2032016, "num_examples": 739, "dataset_name": "iapp_wiki_qa_squad"}}, "download_checksums": {"https://github.com/iapp-technology/iapp-wiki-qa-dataset/raw/main/squad_format/data.zip": {"num_bytes": 2876630, "checksum": "a3530ceafd3b39757fc9720ee0e04f1454e6775bec0c8641964427567fafb214"}}, "download_size": 2876630, "post_processing_size": null, "dataset_size": 20260325, "size_in_bytes": 23136955}}

dummy/iapp_wiki_qa_squad/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7f1a4b703afb0ef0bcf591b877d9ab743034bbe00dad7b054e30acac5e79f235
+size 6376

iapp_wiki_qa_squad.py

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+from __future__ import absolute_import, division, print_function
+
+import json
+import os
+
+import datasets
+
+
+_CITATION = """\
+@dataset{kobkrit_viriyayudhakorn_2021_4539916,
+  author       = {Kobkrit Viriyayudhakorn and
+                  Charin Polpanumas},
+  title        = {iapp_wiki_qa_squad},
+  month        = feb,
+  year         = 2021,
+  publisher    = {Zenodo},
+  version      = 1,
+  doi          = {10.5281/zenodo.4539916},
+  url          = {https://doi.org/10.5281/zenodo.4539916}
+}
+"""
+
+_DESCRIPTION = """\
+`iapp_wiki_qa_squad` is an extractive question answering dataset from Thai Wikipedia articles.
+It is adapted from [the original iapp-wiki-qa-dataset](https://github.com/iapp-technology/iapp-wiki-qa-dataset)
+to [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format, resulting in
+5761/742/739 questions from 1529/191/192 articles.
+"""
+
+
+class IappWikiQaSquadConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        """BuilderConfig
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(IappWikiQaSquadConfig, self).__init__(**kwargs)
+
+
+class IappWikiQaSquad(datasets.GeneratorBasedBuilder):
+    _DOWNLOAD_URL = "https://github.com/iapp-technology/iapp-wiki-qa-dataset/raw/main/squad_format/data.zip"
+    _TRAIN_FILE = "train.jsonl"
+    _VALID_FILE = "valid.jsonl"
+    _TEST_FILE = "test.jsonl"
+
+    BUILDER_CONFIGS = [
+        IappWikiQaSquadConfig(
+            name="iapp_wiki_qa_squad",
+            version=datasets.Version("1.0.0"),
+            description=_DESCRIPTION,
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # datasets.features.FeatureConnectors
+            features=datasets.Features(
+                {
+                    "question_id": datasets.Value("string"),
+                    "article_id": datasets.Value("string"),
+                    "title": datasets.Value("string"),
+                    "context": datasets.Value("string"),
+                    "question": datasets.Value("string"),
+                    "answers": datasets.features.Sequence(
+                        {
+                            "text": datasets.Value("string"),
+                            "answer_start": datasets.Value("int32"),
+                            "answer_end": datasets.Value("int32"),
+                        }
+                    ),
+                }
+            ),
+            # 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,
+            # Homepage of the dataset for documentation
+            homepage="https://github.com/iapp-technology/iapp-wiki-qa-dataset/",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        arch_path = dl_manager.download_and_extract(self._DOWNLOAD_URL)
+        data_dir = os.path.join(arch_path, "data")
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": os.path.join(data_dir, self._TRAIN_FILE)},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": os.path.join(data_dir, self._VALID_FILE)},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": os.path.join(data_dir, self._TEST_FILE)},
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        with open(filepath, encoding="utf-8") as f:
+            for id_, row in enumerate(f):
+                data = json.loads(row)
+
+                yield id_, {
+                    "question_id": data["question_id"],
+                    "article_id": data["article_id"],
+                    "title": data["title"],
+                    "context": data["context"],
+                    "question": data["question"],
+                    "answers": {
+                        "text": data["answers"]["text"],
+                        "answer_start": data["answers"]["answer_start"],
+                        "answer_end": data["answers"]["answer_end"],
+                    },
+                }