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README.md

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----
-task_categories:
-- text-classification
-multilinguality:
-- multilingual
-task_ids: []
-language:
-- awa
-- bho
-- bra
-- hi
-- mag
-language_creators:
-- found
-annotations_creators:
-- no-annotation
-source_datasets:
-- original
-size_categories:
-- 10K<n<100K
-license:
-- cc-by-4.0
-paperswithcode_id: null
-pretty_name: ilist
-tags:
-- language-identification
-dataset_info:
-  features:
-  - name: language_id
-    dtype:
-      class_label:
-        names:
-          0: AWA
-          1: BRA
-          2: MAG
-          3: BHO
-          4: HIN
-  - name: text
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 14362998
-    num_examples: 70351
-  - name: test
-    num_bytes: 2146857
-    num_examples: 9692
-  - name: validation
-    num_bytes: 2407643
-    num_examples: 10329
-  download_size: 18284850
-  dataset_size: 18917498
----
-
-# Dataset Card for ilist
-
-## 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:**
-- **Repository:** https://github.com/kmi-linguistics/vardial2018
-- **Paper:** [Language Identification and Morphosyntactic Tagging: The Second VarDial Evaluation Campaign](https://aclanthology.org/W18-3901/)
-- **Leaderboard:**
-- **Point of Contact:** [email protected]
-
-### Dataset Summary
-
-This dataset is introduced in a task which aimed at identifying 5 closely-related languages of Indo-Aryan language family: Hindi (also known as Khari Boli), Braj Bhasha, Awadhi, Bhojpuri and Magahi. These languages form part of a continuum starting from Western Uttar Pradesh (Hindi and Braj Bhasha) to Eastern Uttar Pradesh (Awadhi and Bhojpuri) and the neighbouring Eastern state of Bihar (Bhojpuri and Magahi).
-
-For this task, participants were provided with a dataset of approximately 15,000 sentences in each language, mainly from the domain of literature, published over the web as well as in print.
-
-### Supported Tasks and Leaderboards
-
-[More Information Needed]
-
-### Languages
-
- Hindi, Braj Bhasha, Awadhi, Bhojpuri and Magahi
-
-## Dataset Structure
-
-### Data Instances
-
-```
-{
-    "language_id": 4,
-    "text": 'तभी बारिश हुई थी जिसका गीलापन इन मूर्तियों को इन तस्वीरों में एक अलग रूप देता है .'
-}
-```
-
-### Data Fields
-
-- `text`: text which you want to classify
-- `language_id`: label for the text as an integer from 0 to 4
-The language ids correspond to the following languages: "AWA", "BRA", "MAG", "BHO", "HIN".
-
-### Data Splits
-
-|                      | train | valid | test  |
-|----------------------|-------|-------|-------|
-| # of input sentences | 70351 | 9692  | 10329 |
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More Information Needed]
-
-### Source Data
-
-The data for this task was collected from both hard printed and digital sources. Printed materials were
-obtained from different institutions that promote these languages. We also gathered data from libraries,
-as well as from local literary and cultural groups. We collected printed stories, novels and essays in
-books, magazines, and newspapers.
-
-#### Initial Data Collection and Normalization
-
-We scanned the printed materials, then we performed OCR, and
-finally we asked native speakers of the respective languages to correct the OCR output. Since there are
-no specific OCR models available for these languages, we used the Google OCR for Hindi, part of the
-Drive API. Since all the languages used the Devanagari script, we expected the OCR to work reasonably
-well, and overall it did. We further managed to get some blogs in Magahi and Bhojpuri.
-
-#### 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
-
-This work is licensed under a Creative Commons Attribution 4.0 International License: http://creativecommons.org/licenses/by/4.0/
-
-### Citation Information
-
-```
-@inproceedings{zampieri-etal-2018-language,
-    title = "Language Identification and Morphosyntactic Tagging: The Second {V}ar{D}ial Evaluation Campaign",
-    author = {Zampieri, Marcos  and
-      Malmasi, Shervin  and
-      Nakov, Preslav  and
-      Ali, Ahmed  and
-      Shon, Suwon  and
-      Glass, James  and
-      Scherrer, Yves  and
-      Samard{\v{z}}i{\'c}, Tanja  and
-      Ljube{\v{s}}i{\'c}, Nikola  and
-      Tiedemann, J{\"o}rg  and
-      van der Lee, Chris  and
-      Grondelaers, Stefan  and
-      Oostdijk, Nelleke  and
-      Speelman, Dirk  and
-      van den Bosch, Antal  and
-      Kumar, Ritesh  and
-      Lahiri, Bornini  and
-      Jain, Mayank},
-    booktitle = "Proceedings of the Fifth Workshop on {NLP} for Similar Languages, Varieties and Dialects ({V}ar{D}ial 2018)",
-    month = aug,
-    year = "2018",
-    address = "Santa Fe, New Mexico, USA",
-    publisher = "Association for Computational Linguistics",
-    url = "https://aclanthology.org/W18-3901",
-    pages = "1--17",
-}
-```
-
-### Contributions
-
-Thanks to [@vasudevgupta7](https://github.com/vasudevgupta7) for adding this dataset.

dataset_infos.json

@@ -1 +0,0 @@
-{"default": {"description": "This dataset is introduced in a task which aimed at identifying 5 closely-related languages of Indo-Aryan language family \u2013\nHindi (also known as Khari Boli), Braj Bhasha, Awadhi, Bhojpuri, and Magahi.\n", "citation": "\\\n@inproceedings{zampieri-etal-2018-language,\n    title = \"Language Identification and Morphosyntactic Tagging: The Second {V}ar{D}ial Evaluation Campaign\",\n    author = {Zampieri, Marcos  and\n      Malmasi, Shervin  and\n      Nakov, Preslav  and\n      Ali, Ahmed  and\n      Shon, Suwon  and\n      Glass, James  and\n      Scherrer, Yves  and\n      Samard{\\v{z}}i{\\'c}, Tanja  and\n      Ljube{\\v{s}}i{\\'c}, Nikola  and\n      Tiedemann, J{\\\"o}rg  and\n      van der Lee, Chris  and\n      Grondelaers, Stefan  and\n      Oostdijk, Nelleke  and\n      Speelman, Dirk  and\n      van den Bosch, Antal  and\n      Kumar, Ritesh  and\n      Lahiri, Bornini  and\n      Jain, Mayank},\n    booktitle = \"Proceedings of the Fifth Workshop on {NLP} for Similar Languages, Varieties and Dialects ({V}ar{D}ial 2018)\",\n    month = aug,\n    year = \"2018\",\n    address = \"Santa Fe, New Mexico, USA\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/W18-3901\",\n    pages = \"1--17\",\n}\n", "homepage": "https://github.com/kmi-linguistics/vardial2018", "license": "", "features": {"language_id": {"num_classes": 5, "names": ["AWA", "BRA", "MAG", "BHO", "HIN"], "id": null, "_type": "ClassLabel"}, "text": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "text-classification", "text_column": "text", "label_column": "language_id"}], "builder_name": "ilist", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 14362998, "num_examples": 70351, "dataset_name": "ilist"}, "test": {"name": "test", "num_bytes": 2146857, "num_examples": 9692, "dataset_name": "ilist"}, "validation": {"name": "validation", "num_bytes": 2407643, "num_examples": 10329, "dataset_name": "ilist"}}, "download_checksums": {"https://raw.githubusercontent.com/kmi-linguistics/vardial2018/master/dataset/train.txt": {"num_bytes": 13870509, "checksum": "1bd3ae96dc17ce44278cff256972649b510d6d8595f420e95bc8284f207e2678"}, "https://raw.githubusercontent.com/kmi-linguistics/vardial2018/master/dataset/gold.txt": {"num_bytes": 2079009, "checksum": "72909da09ed1c1f3710c879ca5b69282e483ce60fe7d90497cfbca46016da704"}, "https://raw.githubusercontent.com/kmi-linguistics/vardial2018/master/dataset/dev.txt": {"num_bytes": 2335332, "checksum": "2ef7944502bb2ee49358873e5d9de241f0a8a8b8a9b88e3e8c37873afd783797"}}, "download_size": 18284850, "post_processing_size": null, "dataset_size": 18917498, "size_in_bytes": 37202348}}

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ilist.py

@@ -1,117 +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.
-"""Indo-Aryan Language Identification Shared Task Dataset"""
-
-
-import datasets
-from datasets.tasks import TextClassification
-
-
-_CITATION = r"""\
-@inproceedings{zampieri-etal-2018-language,
-    title = "Language Identification and Morphosyntactic Tagging: The Second {V}ar{D}ial Evaluation Campaign",
-    author = {Zampieri, Marcos  and
-      Malmasi, Shervin  and
-      Nakov, Preslav  and
-      Ali, Ahmed  and
-      Shon, Suwon  and
-      Glass, James  and
-      Scherrer, Yves  and
-      Samard{\v{z}}i{\'c}, Tanja  and
-      Ljube{\v{s}}i{\'c}, Nikola  and
-      Tiedemann, J{\"o}rg  and
-      van der Lee, Chris  and
-      Grondelaers, Stefan  and
-      Oostdijk, Nelleke  and
-      Speelman, Dirk  and
-      van den Bosch, Antal  and
-      Kumar, Ritesh  and
-      Lahiri, Bornini  and
-      Jain, Mayank},
-    booktitle = "Proceedings of the Fifth Workshop on {NLP} for Similar Languages, Varieties and Dialects ({V}ar{D}ial 2018)",
-    month = aug,
-    year = "2018",
-    address = "Santa Fe, New Mexico, USA",
-    publisher = "Association for Computational Linguistics",
-    url = "https://aclanthology.org/W18-3901",
-    pages = "1--17",
-}
-"""
-
-_DESCRIPTION = """\
-This dataset is introduced in a task which aimed at identifying 5 closely-related languages of Indo-Aryan language family –
-Hindi (also known as Khari Boli), Braj Bhasha, Awadhi, Bhojpuri, and Magahi.
-"""
-
-_URL = "https://raw.githubusercontent.com/kmi-linguistics/vardial2018/master/dataset/{}.txt"
-
-
-class Ilist(datasets.GeneratorBasedBuilder):
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "language_id": datasets.ClassLabel(names=["AWA", "BRA", "MAG", "BHO", "HIN"]),
-                    "text": datasets.Value("string"),
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://github.com/kmi-linguistics/vardial2018",
-            citation=_CITATION,
-            task_templates=[TextClassification(text_column="text", label_column="language_id")],
-        )
-
-    def _split_generators(self, dl_manager):
-        filepaths = dl_manager.download_and_extract(
-            {
-                "train": _URL.format("train"),
-                "test": _URL.format("gold"),
-                "dev": _URL.format("dev"),
-            }
-        )
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": filepaths["train"],
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": filepaths["test"],
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": filepaths["dev"],
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        with open(filepath, "r", encoding="utf-8") as file:
-            for idx, row in enumerate(file):
-                row = row.strip("\n").split("\t")
-                if len(row) == 1:
-                    continue
-                yield idx, {"language_id": row[1], "text": row[0]}