adding the files

README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- expert-generated
+languages:
+- fa
+licenses:
+- cc-by-nc-sa-4.0
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K
+source_datasets:
+- extended|wikipedia|google
+task_categories:
+- question-answering
+task_ids:
+- extractive-qa
+---
+
+# Dataset Card for PersiNLU (Reading Comprehension)
+
+## Table of Contents
+- [Dataset Card for PersiNLU (Reading Comprehension)](#dataset-card-for-persi_nlu_reading_comprehension)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+    - [Annotations](#annotations)
+      - [Annotation process](#annotation-process)
+      - [Who are the annotators?](#who-are-the-annotators)
+    - [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:** [Github](https://github.com/persiannlp/parsinlu/)
+- **Repository:** [Github](https://github.com/persiannlp/parsinlu/)
+- **Paper:** [Arxiv](https://arxiv.org/abs/2012.06154)
+- **Leaderboard:** 
+- **Point of Contact:** d.khashabi@gmail.com
+
+### Dataset Summary
+
+A Persian reading comprehenion task (generating an answer, given a question and a context paragraph). 
+The questions are mined using Google auto-complete, their answers and the corresponding evidence documents are manually annotated by native speakers. 
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+The text dataset is in Persian (`fa`).
+
+## Dataset Structure
+
+### Data Instances
+
+Here is an example from the dataset: 
+```
+{
+    'question': 'پیامبر در چه سالی به پیامبری رسید؟', 
+    'url': 'https://fa.wikipedia.org/wiki/%D9%85%D8%AD%D9%85%D8%AF', 
+    'passage': 'محمد که از روش زندگی مردم مکه ناخشنود بود، گهگاه در غار حرا در یکی از کوه\u200cهای اطراف آن دیار به تفکر و عبادت می\u200cپرداخت. به باور مسلمانان، محمد در همین مکان و در حدود ۴۰ سالگی از طرف خدا به پیامبری برگزیده، و وحی بر او فروفرستاده شد. در نظر آنان، دعوت محمد همانند دعوت دیگر پیامبرانِ کیش یکتاپرستی مبنی بر این بود که خداوند (الله) یکتاست و تسلیم شدن برابر خدا راه رسیدن به اوست.', 
+    'answers': [
+        {'answer_start': 160, 'answer_text': 'حدود ۴۰ سالگی'}
+     ]
+}
+```
+
+### Data Fields
+
+- `question`: the question, mined using Google auto-complete. 
+- `passage`: the passage that contains the answer. 
+- `url`: the url from which the passage was mined. 
+- `answers`: a list of answers, containing the string and the index of the answer.  
+
+### Data Splits
+
+The train/test split contains 600/575 samples.
+
+## Dataset Creation
+
+### Curation Rationale
+
+The question were collected via Google auto-complete.
+The answers were annotated by native speakers. 
+For more details, check [the corresponding draft](https://arxiv.org/abs/2012.06154).
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+CC BY-NC-SA 4.0 License 
+
+### Citation Information
+```bibtex 
+@article{huggingface:dataset,
+    title = {ParsiNLU: A Suite of Language Understanding Challenges for Persian},
+    authors = {Khashabi, Daniel and Cohan, Arman and Shakeri, Siamak and Hosseini, Pedram and Pezeshkpour, Pouya and Alikhani, Malihe and Aminnaseri, Moin and Bitaab, Marzieh and Brahman, Faeze and Ghazarian, Sarik and others},
+    year={2020}
+    journal = {arXiv e-prints},
+    eprint = {2012.06154},    
+}
+```
+
+### Contributions
+
+Thanks to [@danyaljj](https://github.com/danyaljj) for adding this dataset.

dataset_infos.json

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+{"parsinlu-repo": {"description": "A Persian reading comprehenion task (generating an answer, given a question and a context paragraph). \nThe questions are mined using Google auto-complete, their answers and the corresponding evidence documents are manually annotated by native speakers.    \n", "citation": "@article{huggingface:dataset,\n    title = {ParsiNLU: A Suite of Language Understanding Challenges for Persian},\n    authors = {Khashabi, Daniel and Cohan, Arman and Shakeri, Siamak and Hosseini, Pedram and Pezeshkpour, Pouya and Alikhani, Malihe and Aminnaseri, Moin and Bitaab, Marzieh and Brahman, Faeze and Ghazarian, Sarik and others},\n    year={2020}\n    journal = {arXiv e-prints},\n    eprint = {2012.06154},    \n}\n", "homepage": "https://github.com/persiannlp/parsinlu/", "license": "CC BY-NC-SA 4.0", "features": {"question": {"dtype": "string", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "answers": {"feature": {"answer_start": {"dtype": "int32", "id": null, "_type": "Value"}, "answer_text": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "parsinlu_reading_comprehension", "config_name": "parsinlu-repo", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 747679, "num_examples": 600, "dataset_name": "parsinlu_reading_comprehension"}, "test": {"name": "test", "num_bytes": 681945, "num_examples": 575, "dataset_name": "parsinlu_reading_comprehension"}, "validation": {"name": "validation", "num_bytes": 163185, "num_examples": 125, "dataset_name": "parsinlu_reading_comprehension"}}, "download_checksums": {"https://raw.githubusercontent.com/persiannlp/parsinlu/master/data/reading_comprehension/train.jsonl": {"num_bytes": 1933004, "checksum": "488fa21f303d880b82b8ba590e0c5a5b61dfb1442a96aa2db19f487a16f5e480"}, "https://raw.githubusercontent.com/persiannlp/parsinlu/master/data/reading_comprehension/dev.jsonl": {"num_bytes": 424640, "checksum": "6ce2aed6d8ace6ed7f9ef4db9baba3b5efdfa9f99d605dccb494ce39cd63c9c6"}, "https://raw.githubusercontent.com/persiannlp/parsinlu/master/data/reading_comprehension/eval.jsonl": {"num_bytes": 1760219, "checksum": "95ac9cec4548cb35a5b7b2d85dabbd89fe0e724245935fdeeaddea3c07e644fe"}}, "download_size": 4117863, "post_processing_size": null, "dataset_size": 1592809, "size_in_bytes": 5710672}}

parsinlu_reading_comprehension.py

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+# coding=utf-8
+# 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.
+"""ParsiNLU Persian reading comprehension task"""
+
+from __future__ import absolute_import, division, print_function
+
+import json
+
+import datasets
+
+
+logger = datasets.logging.get_logger(__name__)
+
+_CITATION = """\
+@article{huggingface:dataset,
+    title = {ParsiNLU: A Suite of Language Understanding Challenges for Persian},
+    authors = {Khashabi, Daniel and Cohan, Arman and Shakeri, Siamak and Hosseini, Pedram and Pezeshkpour, Pouya and Alikhani, Malihe and Aminnaseri, Moin and Bitaab, Marzieh and Brahman, Faeze and Ghazarian, Sarik and others},
+    year={2020}
+    journal = {arXiv e-prints},
+    eprint = {2012.06154},    
+}
+"""
+
+# You can copy an official description
+_DESCRIPTION = """\
+A Persian reading comprehenion task (generating an answer, given a question and a context paragraph). 
+The questions are mined using Google auto-complete, their answers and the corresponding evidence documents are manually annotated by native speakers.    
+"""
+
+_HOMEPAGE = "https://github.com/persiannlp/parsinlu/"
+
+_LICENSE = "CC BY-NC-SA 4.0"
+
+_URL = "https://raw.githubusercontent.com/persiannlp/parsinlu/master/data/reading_comprehension/"
+_URLs = {
+    "train": _URL + "train.jsonl",
+    "dev": _URL + "dev.jsonl",
+    "test": _URL + "eval.jsonl",
+}
+
+
+class ParsinluReadingComprehension(datasets.GeneratorBasedBuilder):
+    """ParsiNLU Persian reading comprehension task."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="parsinlu-repo", version=VERSION, description="ParsiNLU repository: reading-comprehension"
+        ),
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "question": datasets.Value("string"),
+                "url": datasets.Value("string"),
+                "context": datasets.Value("string"),
+                "answers": datasets.features.Sequence(
+                    {
+                        "answer_start": datasets.Value("int32"),
+                        "answer_text": datasets.Value("string"),
+                    }
+                ),
+            }
+        )
+
+        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=features,  # Here we define them above because they are different between the two configurations
+            # 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=_HOMEPAGE,
+            # License for the dataset if available
+            license=_LICENSE,
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        data_dir = dl_manager.download_and_extract(_URLs)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": data_dir["train"],
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"filepath": data_dir["test"], "split": "test"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": data_dir["dev"],
+                    "split": "dev",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        logger.info("generating examples from = %s", filepath)
+
+        def get_answer_index(passage, answer):
+            return passage.index(answer) if answer in passage else -1
+
+        with open(filepath, encoding="utf-8") as f:
+            for id_, row in enumerate(f):
+                data = json.loads(row)
+                answer = data["answers"]
+                if type(answer[0]) == str:
+                    answer = [{"answer_start": get_answer_index(data["passage"], x), "answer_text": x} for x in answer]
+                else:
+                    answer = [{"answer_start": x[0], "answer_text": x[1]} for x in answer]
+                yield id_, {
+                    "question": data["question"],
+                    "url": str(data["url"]),
+                    "context": data["passage"],
+                    "answers": answer,
+                }