formality
rl-lm-formality-promptspavlick-formality-scoresThis dataset contains sentence-level formality annotations used in the 2016
TACL paper "An Empirical Analysis of Formality in Online Communication"
(Pavlick and Tetreault, 2016). It includes sentences from four genres (news,
blogs, email, and QA forums), all annotated by humans on Amazon Mechanical
Turk. The news and blog data was collected by Shibamouli Lahiri, and we are
redistributing it here for the convenience of other researchers. We collected
the email and answers data ourselves, using… See the full description on the dataset page: https://huggingface.co/datasets/osyvokon/pavlick-formality-scores.ukr_formalityukr-formality-dataset-translated-gyafc
Ukrainian Formality Dataset (translated)
We obtained the first of its kind Ukrainian Formality Classification dataset by trainslating English GYAFC data.
Dataset formation:
English data source: https://aclanthology.org/N18-1012/
Translation into Ukrainian language using model: https://huggingface.co/facebook/nllb-200-distilled-600M
Additionally, the dataset was balanced.
Labels: 0 - informal, 1 - formal.
Load dataset:
from datasets import load_dataset… See the full description on the dataset page: https://huggingface.co/datasets/ukr-detect/ukr-formality-dataset-translated-gyafc.PersonaSignal-LeakageCheck-Communication-Formality-gpt-4omultilingual-formality-transfer
Foreign Language Formal/Informal Translation Dataset
Dataset Description
The multilingual-formality-transfer Dataset is a multilingual resource that provides pairs of texts in their original colloquial/informal form along with their formal counterparts in the same language. The dataset covers multiple languages and was created to support style transfer tasks, specifically formal-informal text transformations while preserving the meaning of the original text.
Each entry… See the full description on the dataset page: https://huggingface.co/datasets/portex/multilingual-formality-transfer.