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README.md

@@ -1,194 +0,0 @@
----
-annotations_creators:
-- expert-generated
-language_creators:
-- expert-generated
-language:
-- fa
-license:
-- 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
-paperswithcode_id: null
-pretty_name: PersiNLU (Reading Comprehension)
-dataset_info:
-  features:
-  - name: question
-    dtype: string
-  - name: url
-    dtype: string
-  - name: context
-    dtype: string
-  - name: answers
-    sequence:
-    - name: answer_start
-      dtype: int32
-    - name: answer_text
-      dtype: string
-  config_name: parsinlu-repo
-  splits:
-  - name: train
-    num_bytes: 747679
-    num_examples: 600
-  - name: test
-    num_bytes: 681945
-    num_examples: 575
-  - name: validation
-    num_bytes: 163185
-    num_examples: 125
-  download_size: 4117863
-  dataset_size: 1592809
----
-
-# Dataset Card for PersiNLU (Reading Comprehension)
-
-## 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)
-  - [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:** [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:** [email](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 with the fields `answer_start` and `answer_text`. Note that in the test set, some `answer_start` values are missing and replaced with `-1`
-
-### 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
-
-Dataset provided for research purposes only. Please check dataset license for additional information.
-
-## 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

@@ -1 +0,0 @@
-{"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}}

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parsinlu_reading_comprehension.py

@@ -1,141 +0,0 @@
-# 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"""
-
-
-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,
-                }