Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Languages:
Polish
Size:
10K - 100K
License:
File size: 4,447 Bytes
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---
annotations_creators:
- found
language_creators:
- found
languages:
- pl
licenses:
- cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-scoring
- text-scoring
paperswithcode_id: allegro-reviews
pretty_name: Allegro Reviews
---
# Dataset Card for [Dataset Name]
## 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:**
https://klejbenchmark.com/
- **Repository:**
https://github.com/allegro/klejbenchmark-allegroreviews
- **Paper:**
KLEJ: Comprehensive Benchmark for Polish Language Understanding (Rybak, Piotr and Mroczkowski, Robert and Tracz, Janusz and Gawlik, Ireneusz)
- **Leaderboard:**
https://klejbenchmark.com/leaderboard/
- **Point of Contact:**
klejbenchmark@allegro.pl
### Dataset Summary
Allegro Reviews is a sentiment analysis dataset, consisting of 11,588 product reviews written in Polish and extracted from Allegro.pl - a popular e-commerce marketplace. Each review contains at least 50 words and has a rating on a scale from one (negative review) to five (positive review).
We recommend using the provided train/dev/test split. The ratings for the test set reviews are kept hidden. You can evaluate your model using the online evaluation tool available on klejbenchmark.com.
### Supported Tasks and Leaderboards
Product reviews sentiment analysis.
https://klejbenchmark.com/leaderboard/
### Languages
Polish
## Dataset Structure
### Data Instances
Two tsv files (train, dev) with two columns (text, rating) and one (test) with just one (text).
### Data Fields
- text: a product review of at least 50 words
- rating: product rating of a scale of one (negative review) to five (positive review)
### Data Splits
Data is splitted in train/dev/test split.
## Dataset Creation
### Curation Rationale
This dataset is one of nine evaluation tasks to improve polish language processing.
### Source Data
#### Initial Data Collection and Normalization
The Allegro Reviews is a set of product reviews from a popular e-commerce marketplace (Allegro.pl).
#### Who are the source language producers?
Customers of an e-commerce marketplace.
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### 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
Allegro Machine Learning Research team klejbenchmark@allegro.pl
### Licensing Information
Dataset licensed under CC BY-SA 4.0
### Citation Information
@inproceedings{rybak-etal-2020-klej,
title = "{KLEJ}: Comprehensive Benchmark for Polish Language Understanding",
author = "Rybak, Piotr and Mroczkowski, Robert and Tracz, Janusz and Gawlik, Ireneusz",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2020.acl-main.111",
pages = "1191--1201",
}
### Contributions
Thanks to [@abecadel](https://github.com/abecadel) for adding this dataset.
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