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Browse files- README.md +155 -0
- dev.jsonl +0 -0
- parafraseja.py +100 -0
- test.jsonl +0 -0
- train.jsonl +0 -0
README.md
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---
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annotations_creators:
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- CLiC-UB
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language_creators:
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- found
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language:
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- ca
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license:
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- cc-by-nc-nd-4.0
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multilinguality:
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- monolingual
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pretty_name: Parafraseja
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size_categories:
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- ?
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task_categories:
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- text-classification
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task_ids:
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- multi-input-text-classification
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---
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# Dataset Card for Parafraseja
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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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- [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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- **Point of Contact:** [blanca.calvo@bsc.es](blanca.calvo@bsc.es)
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### Dataset Summary
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Parafraseja is a dataset of 21,984 pairs of sentences with a label that indicates if they are paraphrases or not. The original sentences were collected from [TE-ca](https://huggingface.co/datasets/projecte-aina/teca) and [STS-ca](https://huggingface.co/datasets/projecte-aina/sts-ca). For each sentence, an annotator wrote a sentence that was a paraphrase and another that was not. The guidelines of this annotation are available.
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### Supported Tasks and Leaderboards
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This dataset is mainly intended to train models for paraphrase detection.
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### Languages
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The dataset is in Catalan (`ca-CA`).
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## Dataset Structure
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The dataset consists of pairs of sentences labelled with "Parafrasis" or "No Parafrasis" in a jsonl format.
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### Data Instances
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<pre>
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{
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"id": "te1_14977_1",
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"source": "teca",
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"original": "La 2a part consta de 23 cap\u00edtols, cadascun dels quals descriu un ocell diferent.",
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"new": "La segona part consisteix en vint-i-tres cap\u00edtols, cada un dels quals descriu un ocell diferent.",
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"label": "Parafrasis"
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}
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</pre>
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### Data Fields
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- original: original sentence
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- new: new sentence, which could be a paraphrase or a non-paraphrase
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- label: relation between original and new
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### Data Splits
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* dev.json: 2,000 examples
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* test.json: 4,000 examples
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* train.json: 15,984 examples
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## Dataset Creation
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### Curation Rationale
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We created this corpus to contribute to the development of language models in Catalan, a low-resource language.
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### Source Data
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The original sentences of this dataset came from the [STS-ca](https://huggingface.co/datasets/projecte-aina/sts-ca) and the [TE-ca](https://huggingface.co/datasets/projecte-aina/teca).
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#### Initial Data Collection and Normalization
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11,543 of the original sentences came from TE-ca, and 10,441 came from STS-ca.
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#### Who are the source language producers?
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TE-ca and STS-ca come from the [Catalan Textual Corpus](https://zenodo.org/record/4519349#.Y1Zs__uxXJF), which consists of several corpora gathered from web crawling and public corpora, and [Vilaweb](https://www.vilaweb.cat), a Catalan newswire.
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### Annotations
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The dataset is annotated with the label "Parafrasis" or "No Parafrasis" for each pair of sentences.
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#### Annotation process
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The annotation process was done by a single annotator and reviewed by another.
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#### Who are the annotators?
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The annotators were Catalan native speakers, with a background on linguistics.
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### Personal and Sensitive Information
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No personal or sensitive information included.
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## Considerations for Using the Data
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### Social Impact of Dataset
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We hope this corpus contributes to the development of language models in Catalan, a low-resource language.
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### Discussion of Biases
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We are aware that this data might contain biases. We have not applied any steps to reduce their impact.
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### Other Known Limitations
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[N/A]
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## Additional Information
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### Dataset Curators
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Text Mining Unit (TeMU) at the Barcelona Supercomputing Center (bsc-temu@bsc.es)
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This work was funded by the [Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya](https://politiquesdigitals.gencat.cat/ca/inici/index.html#googtrans(ca|en) within the framework of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina).
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### Licensing Information
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[Creative Commons Attribution Non-commercial No-Derivatives 4.0 International](https://creativecommons.org/licenses/by-nc-nd/4.0/).
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### Contributions
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[N/A]
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dev.jsonl
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parafraseja.py
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# Loading script for the ReviewsFinder dataset.
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import json
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import csv
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import datasets
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logger = datasets.logging.get_logger(__name__)
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_CITATION = """ """
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_DESCRIPTION = """ Parafraseja is a dataset of 16,584 pairs of sentences with a label that indicates if they are paraphrases or not. The original sentences were collected from TE-ca and STS-ca. For each sentence, an annotator wrote a sentence that was a paraphrase and another that was not. The guidelines of this annotation are available. """
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_HOMEPAGE = """ https://huggingface.co/datasets/projecte-aina/Parafraseja/ """
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_URL = "https://huggingface.co/datasets/projecte-aina/Parafraseja/resolve/main/"
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_TRAINING_FILE = "train.jsonl"
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_DEV_FILE = "dev.jsonl"
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_TEST_FILE = "test.jsonl"
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class ParafrasejaConfig(datasets.BuilderConfig):
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""" Builder config for the Parafraseja dataset """
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def __init__(self, **kwargs):
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"""BuilderConfig for parafrasis.
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Args:
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**kwargs: keyword arguments forwarded to super.
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"""
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super(ParafrasejaConfig, self).__init__(**kwargs)
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class Parafraseja(datasets.GeneratorBasedBuilder):
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""" Parafrasis Dataset """
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BUILDER_CONFIGS = [
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ParafrasejaConfig(
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name="Parafraseja",
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version=datasets.Version("1.0.0"),
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description="Parafraseja dataset",
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),
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]
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"sentence1": datasets.Value("string"),
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"sentence2": datasets.Value("string"),
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"label": datasets.features.ClassLabel
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(names=
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[
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"No Parafrasis",
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"Parafrasis",
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]
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),
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}
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),
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homepage=_HOMEPAGE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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urls_to_download = {
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"train": f"{_URL}{_TRAINING_FILE}",
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"dev": f"{_URL}{_DEV_FILE}",
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"test": f"{_URL}{_TEST_FILE}",
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}
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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(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
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]
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def _generate_examples(self, filepath):
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"""This function returns the examples in the raw (text) form."""
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logger.info("generating examples from = %s", filepath)
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with open(filepath, encoding="utf-8") as f:
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data = [json.loads(line) for line in f]
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for id_, article in enumerate(data):
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yield id_, {
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"sentence1": article['original'],
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"sentence2": article['new'],
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"label": article['label'],
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}
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test.jsonl
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train.jsonl
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