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README.md

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+---
+YAML tags: null
+annotations_creators:
+- professional translators
+- machine-generated
+language:
+- ca
+license:
+- other
+multilinguality:
+- monolingual
+pretty_name: paws-ca
+task_categories:
+- text-classification
+tags:
+- paraphrase-identification
+---
+
+# Dataset Card for PAWS-ca: Paraphrase Adversaries from Word Scrambling in Catalan
+
+## 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:** [PAWS-ca](https://zenodo.org/record/)
+- **Point of Contact:** langtech@bsc.es
+
+### Dataset Summary
+
+The PAWS-ca dataset (Paraphrase Adversaries from Word Scrambling in Catalan) is a translation of the English PAWS dataset into Catalan, commissioned by BSC LangTech Unit.
+
+The dataset contains 4,000 human translated PAWS pairs and 49,000 machine translated pairs.
+
+
+### Supported Tasks and Leaderboards
+
+Paraphrase Identification, Language Model
+
+### Languages
+
+The dataset is in Catalan (`ca-CA`).
+
+## Dataset Structure
+
+### Data Instances
+
+Three JSON files, one for each split.
+
+### Example:
+<pre>
+    
+   {
+       "id": 38
+       "sentence1": Holly estava influenciat musicalment per Elton John.
+       "sentence2": Holly Holly va ser influenciada musicalment per Elton John.
+       "label": 1
+    }
+        
+    {
+        "id":
+        "sentence1": L’equip va respondre als canvis en el següent partit el mateix vespre del 19 de febrer.
+        "sentence2": L'equip va respondre als canvis en el mateix partit d’aquell següent 19 de febrer al vespre.
+        "label": 0
+     }
+      
+</pre>
+
+
+### Data Fields
+
+- id: An ID that matches the ID of the source pair of the English PAWS dataset
+- sentence1: The first sentence
+- sentence2: The second sentence
+- label: Label for each pair
+
+
+
+### Data Splits
+
+* paws-ca.train.jsonl: 49,401 examples
+* paws-ca.val.jsonl: 2,000 examples
+* paws-ca.test.jsonl: 2,000 examples
+
+
+> **Caveat**: please note that the dev and test sets of PAWS-X are both sourced
+> from the dev set of PAWS-Wiki. As a consequence, the same `sentence 1` may
+> appear in both the dev and test sets. Nevertheless our data split guarantees
+> that there is no overlap on sentence pairs (`sentence 1` + `sentence 2`)
+> between dev and test.
+
+## Dataset Creation
+
+### Curation Rationale
+
+We created this dataset to contribute to the development of language models in Catalan, a low-resource language.
+
+### Source Data
+
+PAWS (Paraphrase Adversaries from Word Scrambling)
+
+#### Initial Data Collection and Normalization
+
+This dataset is a translation the English PAWS dataset into Catalan, commissioned by BSC LangTech Unit within Projecte AINA.
+
+#### Who are the source language producers?
+
+For more information on how PAWS was created, refer to the paper (), or visit the [PAWS's webpage]().
+
+
+
+### Annotations
+
+#### Annotation process
+
+[N/A]
+
+
+#### Who are the annotators?
+
+This is a translation of the English PAWS dataset and its annotations.
+
+### Personal and Sensitive Information
+
+No personal or sensitive information included.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+We hope this dataset contributes to the development of language models in Catalan, a low-resource language.
+
+### Discussion of Biases
+
+[N/A]
+
+### Other Known Limitations
+
+[N/A]
+
+## Additional Information
+
+### Dataset Curators
+
+Language Technologies Unit at the Barcelona Supercomputing Center (langtech@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
+
+This work is licensed under a ... License
+
+
+### Citation Information
+
+
+DOI 
+
+### Contributions
+
+[N/A]

paws-ca.py

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+# Loading script for the PAWS-ca dataset
+import csv
+
+import datasets
+
+
+_CITATION = """
+
+_DESCRIPTION = """\
+The PAWS-ca dataset (Paraphrase Adversaries from Word Scrambling in Catalan) is a translation of the English PAWS dataset into Catalan, commissioned by BSC LangTech Unit.
+
+This dataset contains 4,000 human translated PAWS pairs and 49,000 machine translated pairs.
+
+"""
+
+_HOMEPAGE = "https://zenodo.org/record/"
+
+_URL = "https://huggingface.co/datasets/projecte-aina/paws-ca/resolve/main/"
+_TRAINING_FILE = "train.json"
+_DEV_FILE = "dev_2k.json"
+_TEST_FILE = "test_2k.json"
+
+
+class PAWSXConfig(datasets.BuilderConfig):
+    """BuilderConfig for PAWSX-ca."""
+
+    def __init__(self, **kwargs):
+        """Constructs a PAWSXConfig.
+        Args:
+            **kwargs: keyword arguments forwarded to super.
+        """
+        super(PAWSXConfig, self).__init__(version=datasets.Version("1.1.0", ""), **kwargs),
+
+
+class PAWSX(datasets.GeneratorBasedBuilder):
+    """PAWS-ca, a Catalan version of PAWS."""
+
+    VERSION = datasets.Version("1.1.0")
+
+    BUILDER_CONFIGS = [
+        PAWSXConfig(
+            name=config_name,
+            description=(f"This config contains samples in {config_name}."),
+        )
+        for config_name in _DATA_OPTIONS
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "id": datasets.Value("int32"),
+                "sentence1": datasets.Value("string"),
+                "sentence2": datasets.Value("string"),
+                "label": datasets.features.ClassLabel(names=["0", "1"]),
+            }
+        )
+        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):
+        """Returns SplitGenerators."""
+        urls_to_download = {
+            "train": f"{_URL}{_TRAIN_FILE}",
+            "val": 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, split):
+        with open(filepath, encoding='utf-8') as f:
+            for i, line in enumerate(f):
+                data = json.loads(line)
+                yield i, {
+                    'id': data['id'],
+                    'sentence1': data['sentence1'],
+                    'sentence2': data['sentence2'],
+                    'label': str(data['label']),
+                }
+
+    

train.json

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