Datasets:
paws-x

	---
	annotations_creators:
	- expert-generated
	- machine-generated
	language_creators:
	- expert-generated
	- machine-generated
	language:
	- de
	- en
	- es
	- fr
	- ja
	- ko
	- zh
	license:
	- other
	multilinguality:
	- multilingual
	size_categories:
	- 10K<n<100K
	source_datasets:
	- extended\|other-paws
	task_categories:
	- text-classification
	task_ids:
	- semantic-similarity-classification
	- semantic-similarity-scoring
	- text-scoring
	- multi-input-text-classification
	paperswithcode_id: paws-x
	pretty_name: 'PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification'
	tags:
	- paraphrase-identification
	dataset_info:
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	features:
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	features:
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	configs:
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	data_files:
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	path: de/train-*
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	path: de/test-*
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	path: de/validation-*
	- config_name: en
	data_files:
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	path: en/train-*
	- split: test
	path: en/test-*
	- split: validation
	path: en/validation-*
	- config_name: es
	data_files:
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	path: es/train-*
	- split: test
	path: es/test-*
	- split: validation
	path: es/validation-*
	- config_name: fr
	data_files:
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	path: fr/train-*
	- split: test
	path: fr/test-*
	- split: validation
	path: fr/validation-*
	- config_name: ja
	data_files:
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	path: ja/train-*
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	path: ja/test-*
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	path: ja/validation-*
	- config_name: ko
	data_files:
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	path: ko/train-*
	- split: test
	path: ko/test-*
	- split: validation
	path: ko/validation-*
	- config_name: zh
	data_files:
	- split: train
	path: zh/train-*
	- split: test
	path: zh/test-*
	- split: validation
	path: zh/validation-*
	---

	# Dataset Card for PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification

	## 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-X](https://github.com/google-research-datasets/paws/tree/master/pawsx)
	- Repository: [PAWS-X](https://github.com/google-research-datasets/paws/tree/master/pawsx)
	- Paper: [PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification](https://arxiv.org/abs/1908.11828)
	- Point of Contact: [Yinfei Yang](yinfeiy@google.com)

	### Dataset Summary

	This dataset contains 23,659 human translated PAWS evaluation pairs and
	296,406 machine translated training pairs in six typologically distinct
	languages: French, Spanish, German, Chinese, Japanese, and Korean. All
	translated pairs are sourced from examples in
	[PAWS-Wiki](https://github.com/google-research-datasets/paws#paws-wiki).

	For further details, see the accompanying paper:
	[PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase
	Identification](https://arxiv.org/abs/1908.11828)

	### Supported Tasks and Leaderboards

	It has been majorly used for paraphrase identification for English and other 6 languages namely French, Spanish, German, Chinese, Japanese, and Korean

	### Languages

	The dataset is in English, French, Spanish, German, Chinese, Japanese, and Korean

	## Dataset Structure

	### Data Instances

	For en:
	```
	id : 1
	sentence1 : In Paris , in October 1560 , he secretly met the English ambassador , Nicolas Throckmorton , asking him for a passport to return to England through Scotland .
	sentence2 : In October 1560 , he secretly met with the English ambassador , Nicolas Throckmorton , in Paris , and asked him for a passport to return to Scotland through England .
	label : 0
	```
	For fr:
	```
	id : 1
	sentence1 : À Paris, en octobre 1560, il rencontra secrètement l'ambassadeur d'Angleterre, Nicolas Throckmorton, lui demandant un passeport pour retourner en Angleterre en passant par l'Écosse.
	sentence2 : En octobre 1560, il rencontra secrètement l'ambassadeur d'Angleterre, Nicolas Throckmorton, à Paris, et lui demanda un passeport pour retourner en Écosse par l'Angleterre.
	label : 0
	```

	### Data Fields

	All files are in tsv format with four columns:

	Column Name \| Data
	:---------- \| :--------------------------------------------------------
	id \| An ID that matches the ID of the source pair in PAWS-Wiki
	sentence1 \| The first sentence
	sentence2 \| The second sentence
	label \| Label for each pair

	The source text of each translation can be retrieved by looking up the ID in the
	corresponding file in PAWS-Wiki.

	### Data Splits

	The numbers of examples for each of the seven languages are shown below:

	Language \| Train \| Dev \| Test
	:------- \| ------: \| -----: \| -----:
	en \| 49,401 \| 2,000 \| 2,000
	fr \| 49,401 \| 2,000 \| 2,000
	es \| 49,401 \| 2,000 \| 2,000
	de \| 49,401 \| 2,000 \| 2,000
	zh \| 49,401 \| 2,000 \| 2,000
	ja \| 49,401 \| 2,000 \| 2,000
	ko \| 49,401 \| 2,000 \| 2,000


	> 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

	Most existing work on adversarial data generation focuses on English. For example, PAWS (Paraphrase Adversaries from Word Scrambling) (Zhang et al., 2019) consists of challenging English paraphrase identification pairs from Wikipedia and Quora. They remedy this gap with PAWS-X, a new dataset of 23,659 human translated PAWS evaluation pairs in six typologically distinct languages: French, Spanish, German, Chinese, Japanese, and Korean. They provide baseline numbers for three models with different capacity to capture non-local context and sentence structure, and using different multilingual training and evaluation regimes. Multilingual BERT (Devlin et al., 2019) fine-tuned on PAWS English plus machine-translated data performs the best, with a range of 83.1-90.8 accuracy across the non-English languages and an average accuracy gain of 23% over the next best model. PAWS-X shows the effectiveness of deep, multilingual pre-training while also leaving considerable headroom as a new challenge to drive multilingual research that better captures structure and contextual information.

	### Source Data

	PAWS (Paraphrase Adversaries from Word Scrambling)

	#### Initial Data Collection and Normalization

	All translated pairs are sourced from examples in [PAWS-Wiki](https://github.com/google-research-datasets/paws#paws-wiki)

	#### Who are the source language producers?

	This dataset contains 23,659 human translated PAWS evaluation pairs and 296,406 machine translated training pairs in six typologically distinct languages: French, Spanish, German, Chinese, Japanese, and Korean.

	### Annotations

	#### Annotation process

	If applicable, describe the annotation process and any tools used, or state otherwise. Describe the amount of data annotated, if not all. Describe or reference annotation guidelines provided to the annotators. If available, provide interannotator statistics. Describe any annotation validation processes.

	#### Who are the annotators?

	The paper mentions the translate team, especially Mengmeng Niu, for the help with the annotations.

	### 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

	List the people involved in collecting the dataset and their affiliation(s). If funding information is known, include it here.

	### Licensing Information

	The dataset may be freely used for any purpose, although acknowledgement of Google LLC ("Google") as the data source would be appreciated. The dataset is provided "AS IS" without any warranty, express or implied. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

	### Citation Information

	```
	@InProceedings{pawsx2019emnlp,
	title = {{PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification}},
	author = {Yang, Yinfei and Zhang, Yuan and Tar, Chris and Baldridge, Jason},
	booktitle = {Proc. of EMNLP},
	year = {2019}
	}
	```
	### Contributions

	Thanks to [@bhavitvyamalik](https://github.com/bhavitvyamalik), [@gowtham1997](https://github.com/gowtham1997) for adding this dataset.