Datasets:
IndicQA test sets
Browse files- .gitignore +1 -0
- IndicQA.py +119 -0
- README.md +155 -0
.gitignore
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.DS_Store
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IndicQA.py
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"""TODO(xquad): Add a description here."""
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import json
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import datasets
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from datasets.tasks import QuestionAnsweringExtractive
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_CITATION = """\
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"""
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_DESCRIPTION = """\
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"""
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_URL = "https://huggingface.co/datasets/ai4bharat/IndicQA/resolve/main/data/"
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_LANG = ["as", "bn", "gu", "hi", "kn", "ml", "mr", "or", "pa", "ta", "te"]
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class IndicqaConfig(datasets.BuilderConfig):
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"""BuilderConfig for Indicqa"""
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def __init__(self, lang, **kwargs):
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"""
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Args:
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lang: string, language for the input text
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**kwargs: keyword arguments forwarded to super.
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"""
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super(IndicqaConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
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self.lang = lang
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class Xquad(datasets.GeneratorBasedBuilder):
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"""TODO(indicqa): Short description of my dataset."""
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# TODO(indicqa): Set up version.
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VERSION = datasets.Version("1.0.0")
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BUILDER_CONFIGS = [IndicqaConfig(name=f"indicqa.{lang}", description=_DESCRIPTION, lang=lang) for lang in _LANG]
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def _info(self):
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# TODO(indicqa): Specifies the datasets.DatasetInfo object
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return datasets.DatasetInfo(
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# This is the description that will appear on the datasets page.
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description=_DESCRIPTION,
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# datasets.features.FeatureConnectors
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features=datasets.Features(
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{
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"id": datasets.Value("string"),
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"context": datasets.Value("string"),
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"question": datasets.Value("string"),
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"answers": datasets.features.Sequence(
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{
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"text": datasets.Value("string"),
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"answer_start": datasets.Value("int32"),
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}
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),
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# These are the features of your dataset like images, labels ...
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}
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),
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# If there's a common (input, target) tuple from the features,
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# specify them here. They'll be used if as_supervised=True in
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# builder.as_dataset.
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supervised_keys=None,
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# Homepage of the dataset for documentation
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homepage="",
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citation=_CITATION,
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task_templates=[
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QuestionAnsweringExtractive(
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question_column="question", context_column="context", answers_column="answers"
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)
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],
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)
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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# TODO(indicqa): Downloads the data and defines the splits
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# dl_manager is a datasets.download.DownloadManager that can be used to
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# download and extract URLs
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urls_to_download = {lang: _URL + f"indicqa.{lang}.json" for lang in _LANG}
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downloaded_files = dl_manager.download_and_extract(urls_to_download)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={"filepath": downloaded_files[self.config.lang]},
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),
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]
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def _generate_examples(self, filepath):
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"""Yields examples."""
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# TODO(indicqa): Yields (key, example) tuples from the dataset
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with open(filepath, encoding="utf-8") as f:
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indicqa = json.load(f)
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id_ = 0
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for article in indicqa["data"]:
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for paragraph in article["paragraphs"]:
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context = paragraph["context"].strip()
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for qa in paragraph["qas"]:
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question = qa["question"].strip()
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answer_starts = [answer["answer_start"] for answer in qa["answers"]]
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answers = [answer["text"].strip() for answer in qa["answers"]]
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# Features currently used are "context", "question", and "answers".
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# Others are extracted here for the ease of future expansions.
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yield id_, {
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"context": context,
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"question": question,
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"id": qa["id"],
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"answers": {
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"answer_start": answer_starts,
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"text": answers,
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},
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}
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id_ += 1
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README.md
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---
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annotations_creators:
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- expert-generated
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language:
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- as
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- bn
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- gu
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- hi
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- kn
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- ml
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- mr
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- or
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- pa
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- ta
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- te
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language_creators:
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- found
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license:
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- cc-by-4.0
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multilinguality:
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- multilingual
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pretty_name: IndicQA
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size_categories:
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- n<1K
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source_datasets:
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- original
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tags: []
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task_categories:
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- question-answering
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task_ids:
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- closed-domain-qa
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---
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# Dataset Card for [Dataset Name]
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## Table of Contents
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- [Table of Contents](#table-of-contents)
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-fields)
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- [Data Splits](#data-splits)
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- [Dataset Creation](#dataset-creation)
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- [Curation Rationale](#curation-rationale)
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- [Source Data](#source-data)
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- [Annotations](#annotations)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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## Dataset Description
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- **Homepage:**
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- **Repository:**
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- **Paper:**
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- **Leaderboard:**
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- **Point of Contact:**
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### Dataset Summary
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[More Information Needed]
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### Supported Tasks and Leaderboards
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[More Information Needed]
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### Languages
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[More Information Needed]
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## Dataset Structure
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### Data Instances
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[More Information Needed]
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### Data Fields
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[More Information Needed]
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### Data Splits
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[More Information Needed]
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## Dataset Creation
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### Curation Rationale
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[More Information Needed]
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### Source Data
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#### Initial Data Collection and Normalization
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[More Information Needed]
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#### Who are the source language producers?
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[More Information Needed]
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### Annotations
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#### Annotation process
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[More Information Needed]
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#### Who are the annotators?
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[More Information Needed]
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### Personal and Sensitive Information
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[More Information Needed]
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed]
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### Discussion of Biases
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[More Information Needed]
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### Other Known Limitations
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[More Information Needed]
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## Additional Information
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### Dataset Curators
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[More Information Needed]
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### Licensing Information
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[More Information Needed]
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### Citation Information
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[More Information Needed]
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### Contributions
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Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.
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