File size: 1,951 Bytes
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license: cc-by-sa-4.0
dataset_info:
features:
- name: id
dtype: string
- name: lp
dtype: string
- name: source
dtype: string
- name: reference
dtype: string
- name: gold_clean
dtype: string
- name: translation
dtype: string
- name: src_lang
dtype: string
- name: tgt_lang
dtype: string
- name: label
dtype: int64
- name: noise_category
dtype: string
- name: noise_pattern
dtype: string
- name: split
dtype: string
splits:
- name: train
num_bytes: 9755128
num_examples: 8800
download_size: 3139078
dataset_size: 9755128
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
language:
- en
- ar
- zh
- he
- fr
- ru
- it
- de
- ko
- cs
- pl
- ta
- km
---
## Dataset Summary
Name: TransClean — A benchmark for detecting and extracting clean translations from LLM outputs.
Description: This dataset contains **synthetic** examples used to evaluate methods for detecting and extracting clean translations produced by large language models. It supports research on translation quality estimation, extraction, and filtering of clean model outputs. More details can be found in our [paper](https://arxiv.org/abs/2609.11399) at WMT26.
Data columns: `translation` is the output generated by LLMs, which might contain noise if directly used for evaluation. Hence, it is the input of noise extraction method to get clean translation. `gold_clean` is the gold clean translation that can be used for computing accuracy metric. `noise_pattern` indicates what kind of noise the `translation` contains. When `noise_pattern` is `none`, it mean it's already a clean translation. When it is `off_topic`, then there is no clean translation to be extracted, hence **an empty string**.
Included files: `synthetic.jsonl` for the synthetic subset only. Please contact us if you need the curated subset `curated_noisy_1100_with_silver.jsonl`.
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