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README.md

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+---
+annotations_creators:
+- CLiC-UB
+language_creators:
+- found
+language:
+- ca
+license:
+- cc-by-nc-nd-4.0
+multilinguality:
+- monolingual
+pretty_name: Parafraseja
+size_categories:
+- ?
+task_categories:
+- text-classification
+task_ids:
+- multi-input-text-classification
+---
+
+# Dataset Card for Parafraseja
+
+## Table of Contents
+- [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)
+  - [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
+
+- **Point of Contact:** [blanca.calvo@bsc.es](blanca.calvo@bsc.es)
+
+### Dataset Summary
+
+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. 
+
+### Supported Tasks and Leaderboards
+
+This dataset is mainly intended to train models for paraphrase detection.
+
+### Languages
+
+The dataset is in Catalan (`ca-CA`).
+
+## Dataset Structure
+
+The dataset consists of pairs of sentences labelled with "Parafrasis" or "No Parafrasis" in a jsonl format.
+
+### Data Instances
+
+<pre>
+  {
+    "id": "te1_14977_1", 
+    "source": "teca", 
+    "original": "La 2a part consta de 23 cap\u00edtols, cadascun dels quals descriu un ocell diferent.", 
+    "new": "La segona part consisteix en vint-i-tres cap\u00edtols, cada un dels quals descriu un ocell diferent.", 
+    "label": "Parafrasis"
+   }
+</pre>
+
+### Data Fields
+- original: original sentence
+- new: new sentence, which could be a paraphrase or a non-paraphrase
+- label: relation between original and new
+
+### Data Splits
+
+* dev.json: 2,000 examples
+* test.json: 4,000 examples
+* train.json: 15,984 examples
+
+## Dataset Creation
+
+### Curation Rationale
+
+We created this corpus to contribute to the development of language models in Catalan, a low-resource language. 
+
+### Source Data
+
+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).
+
+#### Initial Data Collection and Normalization
+
+11,543 of the original sentences came from TE-ca, and 10,441 came from STS-ca.
+
+#### Who are the source language producers?
+
+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.
+
+### Annotations
+
+The dataset is annotated with the label "Parafrasis" or "No Parafrasis" for each pair of sentences.
+
+#### Annotation process
+
+The annotation process was done by a single annotator and reviewed by another. 
+
+#### Who are the annotators?
+
+The annotators were Catalan native speakers, with a background on linguistics.
+
+### Personal and Sensitive Information
+
+No personal or sensitive information included.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+We hope this corpus contributes to the development of language models in Catalan, a low-resource language.
+
+### Discussion of Biases
+
+We are aware that this data might contain biases. We have not applied any steps to reduce their impact.
+
+### Other Known Limitations
+
+[N/A]
+
+## Additional Information
+
+### Dataset Curators
+
+Text Mining Unit (TeMU) at the Barcelona Supercomputing Center (bsc-temu@bsc.es)
+
+
+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).
+
+### Licensing Information
+
+[Creative Commons Attribution Non-commercial No-Derivatives 4.0 International](https://creativecommons.org/licenses/by-nc-nd/4.0/).
+
+
+
+### Contributions
+
+[N/A]

parafraseja.py

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+# Loading script for the ReviewsFinder dataset.
+
+
+import json
+import csv
+
+import datasets
+
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_CITATION = """ """
+
+
+_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.  """
+
+
+_HOMEPAGE = """ https://huggingface.co/datasets/projecte-aina/Parafraseja/ """
+
+
+
+_URL = "https://huggingface.co/datasets/projecte-aina/Parafraseja/resolve/main/"
+_TRAINING_FILE = "train.jsonl"
+_DEV_FILE = "dev.jsonl"
+_TEST_FILE = "test.jsonl"
+
+
+class ParafrasejaConfig(datasets.BuilderConfig):
+    """ Builder config for the Parafraseja dataset """
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for parafrasis.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(ParafrasejaConfig, self).__init__(**kwargs)
+
+
+class Parafraseja(datasets.GeneratorBasedBuilder):
+    """ Parafrasis Dataset """
+
+
+    BUILDER_CONFIGS = [
+        ParafrasejaConfig(
+            name="Parafraseja",
+            version=datasets.Version("1.0.0"),
+            description="Parafraseja dataset",
+        ),
+    ]
+
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "sentence1": datasets.Value("string"),
+                    "sentence2": datasets.Value("string"),
+                    "label": datasets.features.ClassLabel
+                    (names=
+                        [
+                            "No Parafrasis",
+                            "Parafrasis",
+                        ]
+                    ),
+                }
+            ),
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+                
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        urls_to_download = {
+            "train": f"{_URL}{_TRAINING_FILE}",
+            "dev": f"{_URL}{_DEV_FILE}",
+            "test": f"{_URL}{_TEST_FILE}",
+        }
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
+        ]
+
+
+    def _generate_examples(self, filepath):
+        """This function returns the examples in the raw (text) form."""
+        logger.info("generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            data = [json.loads(line) for line in f]
+            for id_, article in enumerate(data):
+                    yield id_, {
+                        "sentence1": article['original'],
+                        "sentence2": article['new'],
+                        "label": article['label'],
+                    }