Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
json
Languages:
Polish
Size:
10K - 100K
License:
File size: 2,317 Bytes
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---
language:
- pl
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
task_categories:
- text-classification
task_ids:
- topic-classification
- multi-class-classification
pretty_name: 8TAGS
dataset_info:
features:
- name: sentence
dtype: string
- name: label
dtype:
class_label:
names:
0: film
1: history
2: food
3: medicine
4: motorization
5: work
6: sport
7: technology
splits:
- name: train
num_bytes: 3765325
num_examples: 40001
- name: validation
num_bytes: 467676
num_examples: 5000
- name: test
num_bytes: 416311
num_examples: 4372
---
# 8TAGS
### Dataset Summary
A Polish topic classification dataset consisting of headlines from social media posts. It contains about 50,000 sentences annotated with 8 topic labels: film, history, food, medicine, motorization, work, sport and technology. This dataset was created automatically by extracting sentences from headlines and short descriptions of articles posted on Polish social networking site **wykop.pl**. The service allows users to annotate articles with one or more tags (categories). Dataset represents a selection of article sentences from 8 popular categories. The resulting corpus contains cleaned and tokenized, unambiguous sentences (tagged with only one of the selected categories), and longer than 30 characters.
### Data Instances
Example instance:
```
{
"sentence": "Kierowca był nieco zdziwiony że podróżując sporo ponad 200 km / h zatrzymali go policjanci.",
"label": "4"
}
```
### Data Fields
- sentence: sentence text
- label: label identifier corresponding to one of 8 topics
### Citation Information
```
@inproceedings{dadas-etal-2020-evaluation,
title = "Evaluation of Sentence Representations in {P}olish",
author = "Dadas, Slawomir and Pere{\l}kiewicz, Micha{\l} and Po{\'s}wiata, Rafa{\l}",
booktitle = "Proceedings of the 12th Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.207",
pages = "1674--1680",
language = "English",
ISBN = "979-10-95546-34-4",
}
```
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