configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: annotator_labels
sequence: string
- name: genre
dtype: string
- name: gold_label
dtype: string
- name: pairID
dtype: string
splits:
- name: train
num_bytes: 92877120
num_examples: 380800
- name: validation
num_bytes: 5903876
num_examples: 19392
- name: test
num_bytes: 5321727
num_examples: 19040
download_size: 58511174
dataset_size: 104102723
license: creativeml-openrail-m
task_categories:
- sentence-similarity
language:
- nl
pretty_name: Dutch MultiNLI(MM) using MariaNMT
size_categories:
- 100K<n<1M
---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: annotator_labels
sequence: string
- name: genre
dtype: string
- name: gold_label
dtype: string
- name: pairID
dtype: string
splits:
- name: train
num_bytes: 92877120
num_examples: 380800
- name: validation
num_bytes: 5903876
num_examples: 19392
- name: test
num_bytes: 5321727
num_examples: 19040
download_size: 58511174
dataset_size: 104102723
---
Dataset Card for "MultiNLI_Dutch_translated_with_Marianmt"
Translation of the English corpus Multi-Genre Natural Language Inference (MultiNLI) corpus , specifically the mismatched version, to Dutch using an Maria NMT model, trained by Helsinki NLP. Note, for reference: Maria NMT is based on BART, described here.
A complete description of the dataset is given here, and is available on HuggingFace.
Attribution
If you use this dataset please use the following to credit the creators of MultiNLI:
@InProceedings{N18-1101,
author = "Williams, Adina
and Nangia, Nikita
and Bowman, Samuel",
title = "A Broad-Coverage Challenge Corpus for
Sentence Understanding through Inference",
booktitle = "Proceedings of the 2018 Conference of
the North American Chapter of the
Association for Computational Linguistics:
Human Language Technologies, Volume 1 (Long
Papers)",
year = "2018",
publisher = "Association for Computational Linguistics",
pages = "1112--1122",
location = "New Orleans, Louisiana",
url = "http://aclweb.org/anthology/N18-1101"
}
The creators of the OPUS-MT models:
@InProceedings{TiedemannThottingal:EAMT2020,
author = {J{\"o}rg Tiedemann and Santhosh Thottingal},
title = {{OPUS-MT} — {B}uilding open translation services for the {W}orld},
booktitle = {Proceedings of the 22nd Annual Conferenec of the European Association for Machine Translation (EAMT)},
year = {2020},
address = {Lisbon, Portugal}
}
and
@misc {van_es_2023,
author = { {Bram van Es} },
title = { MultiNLI_Dutch_translated_with_Marianmt (Revision 284d39a) },
year = 2023,
url = { https://huggingface.co/datasets/UMCU/MultiNLI_Dutch_translated_with_Marianmt },
doi = { 10.57967/hf/1417 },
publisher = { Hugging Face }
}
License
For both the Maria NMT model and the original Helsinki NLP Opus MT model we did not find a license, if this was in error please let us know and we will add the appropriate licensing promptly.
We adopt the licensing of the MultiNLI corpus, which is stated as follows in the accompanying publication: The majority of the corpus is released under the OANC’s license, which allows all content to be freely used, modified, and shared under permissive terms. The data in the FICTION section falls under several permissive licenses; Seven Swords is available under a Creative Commons Share-Alike 3.0 Unported License, and with the explicit permission of the author, Living History and Password Incorrect are available under Creative Commons Attribution 3.0 Unported Licenses; the remaining works of fiction are in the public domain in the United States (but may be licensed differently elsewhere).