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null | null | @software{bact_2019_3457447,
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title = {PyThaiNLP/wisesight-sentiment: First release},
month = sep,
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null | null | @software{bact_2019_3457447,
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Chormai, Pattarawat and
Polpanumas, Charin},
title = {PyThaiNLP/wisesight-sentiment: First release},
month = sep,
year = 2019,
publisher... | Wisesight Sentiment Corpus: Social media messages in Thai language with sentiment category (positive, neutral, negative, question)
* Released to public domain under Creative Commons Zero v1.0 Universal license.
* Category (Labels): {"pos": 0, "neu": 1, "neg": 2, "q": 3}
* Size: 26,737 messages
* Language: Central Thai
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null | null | @InProceedings{bojar-EtAl:2014:W14-33,
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null | null | @InProceedings{bojar-EtAl:2015:WMT,
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null | null | @InProceedings{bojar-EtAl:2016:WMT1,
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null | null | @InProceedings{bojar-EtAl:2017:WMT1,
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null | null | @InProceedings{bojar-EtAl:2018:WMT1,
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and Graham, Yvette and Haddow, Barry and Huck, Matthias and
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null | null | @ONLINE {wmt19translate,
author = {Wikimedia Foundation},
title = {ACL 2019 Fourth Conference on Machine Translation (WMT19), Shared Task: Machine Translation of News},
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null | null | Not available. | This shared task (part of WMT20) will build on its previous editions
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null | null | Not available. | This shared task (part of WMT20) will build on its previous editions
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null | null | Not available. | This shared task (part of WMT20) will build on its previous editions
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null | null | @InProceedings{bojar-EtAl:2014:W14-33,
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... |
null | null | @inproceedings{derczynski-etal-2017-results,
title = "Results of the {WNUT}2017 Shared Task on Novel and Emerging Entity Recognition",
author = "Derczynski, Leon and
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van Erp, Marieke and
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null | null | null | Wongnai's review dataset contains restaurant reviews and ratings, mainly in Thai language.
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pretty_name: WongnaiReviews
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null | null | @misc{wen2017networkbased,
title={A Network-based End-to-End Trainable Task-oriented Dialogue System},
author={Tsung-Hsien Wen and David Vandyke and Nikola Mrksic and Milica Gasic and Lina M. Rojas-Barahona and Pei-Hao Su and Stefan Ultes and Steve Young},
year={2017},
eprint={1604.04562},
... | Wizard-of-Oz (WOZ) is a dataset for training task-oriented dialogue systems. The dataset is designed around the task of finding a restaurant in the Cambridge, UK area. There are three informable slots (food, pricerange,area) that users can use to constrain the search and six requestable slots (address, phone, postcode ... | false | 976 | false | woz_dialogue | 2022-11-03T16:31:44.000Z | wizard-of-oz | false | 951cb769ac2b4d769c059878ac008fb6baa11c04 | [] | [
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null | null | @misc{11321/305,
title = {{WUT} Relations Between Sentences Corpus},
author = {Oleksy, Marcin and Fikus, Dominika and Wolski, Michal and Podbielska, Malgorzata and Turek, Agnieszka and Kędzia, Pawel},
url = {http://hdl.handle.net/11321/305},
note = {{CLARIN}-{PL} digital repository},
copyright = {Attribution-{Shar... | WUT Relations Between Sentences Corpus contains 2827 pairs of related sentences.
Relationships are derived from Cross-document Structure Theory (CST), which enables multi-document summarization through identification of cross-document rhetorical relationships within a cluster of related documents.
Every relation was ma... | false | 320 | false | wrbsc | 2022-11-03T16:07:58.000Z | null | false | 80c6003a80a300c4a85524f8c8e2b959657bb14d | [] | [
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null | null | @inproceedings{vamvas2020xstance,
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booktitle = "Proceedings of the 5th Swiss Text Analytics Conference (SwissText) \\& 16th Conference on Natural Language Processing (KONVENS)"... | The x-stance dataset contains more than 150 political questions, and 67k comments written by candidates on those questions.
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null | null | @article{ponti2020xcopa,
title={{XCOPA: A} Multilingual Dataset for Causal Commonsense Reasoning},
author={Edoardo M. Ponti, Goran Glava\v{s}, Olga Majewska, Qianchu Liu, Ivan Vuli\'{c} and Anna Korhonen},
journal={arXiv preprint},
year={2020},
url={https://ducdauge.github.io/files/xcopa.pdf}
}
@inproceedi... | XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele ... | false | 7,969 | false | xcopa | 2022-11-03T16:46:56.000Z | xcopa | false | 602926940ca50a1cdb407a337e3696992cd76a6f | [] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:et",
"language:ht",
"language:id",
"language:it",
"language:qu",
"language:sw",
"language:ta",
"language:th",
"language:tr",
"language:vi",
"language:zh",
"license:cc-by-4.0",
"multilinguality:multil... | https://huggingface.co/datasets/xcopa/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- et
- ht
- id
- it
- qu
- sw
- ta
- th
- tr
- vi
- zh
license:
- cc-by-4.0
multilinguality:
- multilingual
pretty_name: XCOPA
size_categories:
- unknown
source_datasets:
- extended|copa
task_categories:
- question-answering
ta... |
null | null | # X-CSR
@inproceedings{lin-etal-2021-common,
title = "Common Sense Beyond {E}nglish: Evaluating and Improving Multilingual Language Models for Commonsense Reasoning",
author = "Lin, Bill Yuchen and
Lee, Seyeon and
Qiao, Xiaoyang and
Ren, Xiang",
booktitle = "Proceedings of the 59th Annu... | To evaluate multi-lingual language models (ML-LMs) for commonsense reasoning in a cross-lingual zero-shot transfer setting (X-CSR), i.e., training in English and test in other languages, we create two benchmark datasets, namely X-CSQA and X-CODAH. Specifically, we automatically translate the original CSQA and CODAH dat... | false | 5,246 | false | xcsr | 2022-11-03T16:46:53.000Z | null | false | 512c2be6284195636331305ea30caf3086f7befe | [] | [
"arxiv:2106.06937",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language_creators:machine-generated",
"language:ar",
"language:de",
"language:en",
"language:es",
"language:fr",
"language:hi",
"language:it",
"language:ja",
"language:nl",
"language:pl",
"languag... | https://huggingface.co/datasets/xcsr/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
- machine-generated
language:
- ar
- de
- en
- es
- fr
- hi
- it
- ja
- nl
- pl
- pt
- ru
- sw
- ur
- vi
- zh
license:
- mit
multilinguality:
- multilingual
pretty_name: X-CSR
size_categories:
- 1K<n<10K
source_datasets:
- extended|codah
- exten... |
null | null | @inproceedings{ohman2020xed,
title={XED: A Multilingual Dataset for Sentiment Analysis and Emotion Detection},
author={{\"O}hman, Emily and P{\"a}mies, Marc and Kajava, Kaisla and Tiedemann, J{\"o}rg},
booktitle={The 28th International Conference on Computational Linguistics (COLING 2020)},
year={2020}
} | A multilingual fine-grained emotion dataset. The dataset consists of human annotated Finnish (25k) and English sentences (30k). Plutchik’s
core emotions are used to annotate the dataset with the addition of neutral to create a multilabel multiclass
dataset. The dataset is carefully evaluated using language-specific BER... | false | 1,642 | false | xed_en_fi | 2022-11-03T16:32:01.000Z | xed | false | b06d5f66ab8a6e191f9c90f7e9555e660bc4c86e | [] | [
"arxiv:2011.01612",
"annotations_creators:expert-generated",
"language_creators:found",
"language:en",
"language:fi",
"license:cc-by-4.0",
"multilinguality:multilingual",
"size_categories:10K<n<100K",
"size_categories:1K<n<10K",
"source_datasets:extended|other-OpenSubtitles2016",
"task_categorie... | https://huggingface.co/datasets/xed_en_fi/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
- fi
license:
- cc-by-4.0
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
- 1K<n<10K
source_datasets:
- extended|other-OpenSubtitles2016
task_categories:
- text-classification
task_ids:
- intent-classification
- multi-c... |
null | null | @article{Liang2020XGLUEAN,
title={XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation},
author={Yaobo Liang and Nan Duan and Yeyun Gong and Ning Wu and Fenfei Guo and Weizhen Qi
and Ming Gong and Linjun Shou and Daxin Jiang and Guihong Cao and Xiaodong Fan and Ruofei
Zhan... | XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matchi... | false | 2,424 | false | xglue | 2022-11-03T16:32:36.000Z | null | false | 3c89eff9b63190b26a9f825774eb0500b3d7a429 | [] | [
"arxiv:1907.09190",
"annotations_creators:crowdsourced",
"annotations_creators:expert-generated",
"annotations_creators:found",
"annotations_creators:machine-generated",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"language_creators:found",
"language_creators:machine-gene... | https://huggingface.co/datasets/xglue/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
- expert-generated
- found
- machine-generated
language_creators:
- crowdsourced
- expert-generated
- found
- machine-generated
language:
- ar
- bg
- de
- el
- en
- es
- fr
- hi
- it
- nl
- pl
- pt
- ru
- sw
- th
- tr
- ur
- vi
- zh
license:
- cc-by-nc-4.0
- cc-by-sa-4.0
- other... |
null | null | @InProceedings{conneau2018xnli,
author = {Conneau, Alexis
and Rinott, Ruty
and Lample, Guillaume
and Williams, Adina
and Bowman, Samuel R.
and Schwenk, Holger
and Stoyanov, Veselin},
title = {XNLI: Evaluating Cross... | XNLI is a subset of a few thousand examples from MNLI which has been translated
into a 14 different languages (some low-ish resource). As with MNLI, the goal is
to predict textual entailment (does sentence A imply/contradict/neither sentence
B) and is a classification task (given two sentences, predict one of three
lab... | false | 29,327 | false | xnli | 2022-11-03T16:47:22.000Z | xnli | false | f08747ee4cafc9be157955dd02703c64fa758c82 | [] | [
"language:en"
] | https://huggingface.co/datasets/xnli/resolve/main/README.md | ---
language:
- en
paperswithcode_id: xnli
pretty_name: Cross-lingual Natural Language Inference
dataset_info:
- config_name: ar
features:
- name: premise
dtype: string
- name: hypothesis
dtype: string
- name: label
dtype:
class_label:
names:
0: entailment
1: neutra... |
null | null | @misc{asai2020xor,
title={XOR QA: Cross-lingual Open-Retrieval Question Answering},
author={Akari Asai and Jungo Kasai and Jonathan H. Clark and Kenton Lee and Eunsol Choi and Hannaneh Hajishirzi},
year={2020},
eprint={2010.11856},
archivePrefix={arXiv},
primaryClass={cs.CL}
} | XOR-TyDi QA brings together for the first time information-seeking questions,
open-retrieval QA, and multilingual QA to create a multilingual open-retrieval
QA dataset that enables cross-lingual answer retrieval. It consists of questions
written by information-seeking native speakers in 7 typologically ... | false | 478 | false | xor_tydi_qa | 2022-11-03T16:16:28.000Z | xor-tydi-qa | false | ff984c7c15d6ce086cc8d90024af562f23f80bcf | [] | [
"arxiv:2010.11856",
"annotations_creators:crowdsourced",
"language_creators:expert-generated",
"language_creators:found",
"language:ar",
"language:bn",
"language:fi",
"language:ja",
"language:ko",
"language:ru",
"language:te",
"license:mit",
"multilinguality:multilingual",
"size_categories... | https://huggingface.co/datasets/xor_tydi_qa/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- expert-generated
- found
language:
- ar
- bn
- fi
- ja
- ko
- ru
- te
license:
- mit
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
source_datasets:
- original
- extended|tydiqa
task_categories:
- question-answering
task_ids:
- open-domain-qa
... |
null | null | @article{Artetxe:etal:2019,
author = {Mikel Artetxe and Sebastian Ruder and Dani Yogatama},
title = {On the cross-lingual transferability of monolingual representations},
journal = {CoRR},
volume = {abs/1910.11856},
year = {2019},
archivePrefix = {arXiv},
eprin... | XQuAD (Cross-lingual Question Answering Dataset) is a benchmark dataset for evaluating cross-lingual question answering
performance. The dataset consists of a subset of 240 paragraphs and 1190 question-answer pairs from the development set
of SQuAD v1.1 (Rajpurkar et al., 2016) together with their professional translat... | false | 6,042 | false | xquad | 2022-11-03T16:46:57.000Z | xquad | false | aac5a8a341269b657112009a2bc01e2e2dbf2a0f | [] | [
"arxiv:1910.11856",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:ar",
"language:de",
"language:el",
"language:en",
"language:es",
"language:hi",
"language:ro",
"language:ru",
"language:th",
"language:tr",
"language:vi",
"language:zh",
"licens... | https://huggingface.co/datasets/xquad/resolve/main/README.md | ---
pretty_name: XQuAD
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- ar
- de
- el
- en
- es
- hi
- ro
- ru
- th
- tr
- vi
- zh
license:
- cc-by-sa-4.0
multilinguality:
- multilingual
size_categories:
- unknown
source_datasets:
- extended|squad
task_categories:
- question-ans... |
null | null | @article{roy2020lareqa,
title={LAReQA: Language-agnostic answer retrieval from a multilingual pool},
author={Roy, Uma and Constant, Noah and Al-Rfou, Rami and Barua, Aditya and Phillips, Aaron and Yang, Yinfei},
journal={arXiv preprint arXiv:2004.05484},
year={2020}
} | XQuAD-R is a retrieval version of the XQuAD dataset (a cross-lingual extractive QA dataset). Like XQuAD, XQUAD-R is an 11-way parallel dataset, where each question appears in 11 different languages and has 11 parallel correct answers across the languages. | false | 2,708 | false | xquad_r | 2022-11-03T16:32:39.000Z | xquad-r | false | 66755906572d9939454ce444649cc4935942de9d | [] | [
"arxiv:2004.05484",
"annotations_creators:expert-generated",
"language_creators:found",
"language:ar",
"language:de",
"language:el",
"language:en",
"language:es",
"language:hi",
"language:ru",
"language:th",
"language:tr",
"language:vi",
"language:zh",
"license:cc-by-sa-4.0",
"multilin... | https://huggingface.co/datasets/xquad_r/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ar
- de
- el
- en
- es
- hi
- ru
- th
- tr
- vi
- zh
license:
- cc-by-sa-4.0
multilinguality:
- multilingual
size_categories:
- 1K<n<10K
source_datasets:
- extended|squad
- extended|xquad
task_categories:
- question-answering
task_ids:
... |
null | null | @article{Narayan2018DontGM,
title={Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization},
author={Shashi Narayan and Shay B. Cohen and Mirella Lapata},
journal={ArXiv},
year={2018},
volume={abs/1808.08745}
} | Extreme Summarization (XSum) Dataset.
There are three features:
- document: Input news article.
- summary: One sentence summary of the article.
- id: BBC ID of the article. | false | 63,523 | false | xsum | 2022-11-03T16:47:37.000Z | xsum | false | 1a1b54f33ca0e84572aaa46193105c1b2d02d644 | [] | [
"arxiv:1808.08745",
"annotations_creators:found",
"language_creators:found",
"language:en",
"license:unknown",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"task_categories:summarization",
"task_ids:news-articles-summarization"
] | https://huggingface.co/datasets/xsum/resolve/main/README.md | ---
annotations_creators:
- found
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
pretty_name: Extreme Summarization (XSum)
paperswithcode_id: xsum
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- summarization
task_ids:
- news-articles-summarizatio... |
null | null | @InProceedings{maynez_acl20,
author = "Joshua Maynez and Shashi Narayan and Bernd Bohnet and Ryan Thomas Mcdonald",
title = "On Faithfulness and Factuality in Abstractive Summarization",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
year = ... | Neural abstractive summarization models are highly prone to hallucinate content that is unfaithful to the input
document. The popular metric such as ROUGE fails to show the severity of the problem. The dataset consists of
faithfulness and factuality annotations of abstractive summaries for the XSum dataset. We have cro... | false | 530 | false | xsum_factuality | 2022-11-03T16:16:30.000Z | null | false | d23e8860927524bc8953ce56303bbcf67c6bd024 | [] | [
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:extended|other-xsum",
"task_categories:summarization",
"tags:hallucinations"
] | https://huggingface.co/datasets/xsum_factuality/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- extended|other-xsum
task_categories:
- summarization
task_ids: []
paperswithcode_id: null
pretty_name: XSum Hallucination Annotatio... |
null | null | @article{hu2020xtreme,
author = {Junjie Hu and Sebastian Ruder and Aditya Siddhant and Graham Neubig and Orhan Firat and Melvin Johnson},
title = {XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization},
journal = {CoRR},
volume = {abs/2003.... | The Cross-lingual TRansfer Evaluation of Multilingual Encoders (XTREME) benchmark is a benchmark for the evaluation of
the cross-lingual generalization ability of pre-trained multilingual models. It covers 40 typologically diverse languages
(spanning 12 language families) and includes nine tasks that collectively requi... | false | 40,160 | false | xtreme | 2022-11-03T16:47:27.000Z | xtreme | false | 9be0d5944dc1543c1408e9f59527f80bd1fc9579 | [] | [
"arxiv:2003.11080",
"annotations_creators:found",
"language_creators:found",
"language:af",
"language:ar",
"language:bg",
"language:bn",
"language:de",
"language:el",
"language:en",
"language:es",
"language:et",
"language:eu",
"language:fa",
"language:fi",
"language:fr",
"language:he... | https://huggingface.co/datasets/xtreme/resolve/main/README.md | ---
annotations_creators:
- found
language_creators:
- found
language:
- af
- ar
- bg
- bn
- de
- el
- en
- es
- et
- eu
- fa
- fi
- fr
- he
- hi
- hu
- id
- it
- ja
- jv
- ka
- kk
- ko
- ml
- mr
- ms
- my
- nl
- pt
- ru
- sw
- ta
- te
- th
- tl
- tr
- ur
- vi
- yo
- zh
language_bcp47:
- fa-IR
license:
- apache-2.0
- c... |
null | null | null | Yahoo Non-Factoid Question Dataset is derived from Yahoo's Webscope L6 collection using machine learning techiques such that the questions would contain non-factoid answers.The dataset contains 87,361 questions and their corresponding answers. Each question contains its best answer along with additional other answers s... | false | 826 | false | yahoo_answers_qa | 2022-11-03T16:30:48.000Z | null | false | 6de8ee32edf4ac86393663da286c80e35ebe40b0 | [] | [
"annotations_creators:found",
"language_creators:found",
"language:en",
"license:unknown",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|other-yahoo-webscope-l6",
"task_categories:question-answering",
"task_ids:open-domain-qa"
] | https://huggingface.co/datasets/yahoo_answers_qa/resolve/main/README.md | ---
annotations_creators:
- found
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- extended|other-yahoo-webscope-l6
task_categories:
- question-answering
task_ids:
- open-domain-qa
paperswithcode_id: null
pretty_name: YahooAnswe... |
null | null | null | Yahoo! Answers Topic Classification is text classification dataset. The dataset is the Yahoo! Answers corpus as of 10/25/2007. The Yahoo! Answers topic classification dataset is constructed using 10 largest main categories. From all the answers and other meta-information, this dataset only used the best answer content ... | false | 5,798 | false | yahoo_answers_topics | 2022-11-03T16:46:51.000Z | null | false | 53ee803131fd0f9f6813fb65c7afdfbe26234c49 | [] | [
"annotations_creators:found",
"language_creators:found",
"language:en",
"license:unknown",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:extended|other-yahoo-answers-corpus",
"task_categories:text-classification",
"task_ids:topic-classification"
] | https://huggingface.co/datasets/yahoo_answers_topics/resolve/main/README.md | ---
annotations_creators:
- found
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- extended|other-yahoo-answers-corpus
task_categories:
- text-classification
task_ids:
- topic-classification
paperswithcode_id: null
pretty_name: Ya... |
null | null | @article{zhangCharacterlevelConvolutionalNetworks2015,
archivePrefix = {arXiv},
eprinttype = {arxiv},
eprint = {1509.01626},
primaryClass = {cs},
title = {Character-Level {{Convolutional Networks}} for {{Text Classification}}},
abstract = {This article offers an empirical exploration on the use of character... | Large Yelp Review Dataset.
This is a dataset for binary sentiment classification. We provide a set of 560,000 highly polar yelp reviews for training, and 38,000 for testing.
ORIGIN
The Yelp reviews dataset consists of reviews from Yelp. It is extracted
from the Yelp Dataset Challenge 2015 data. For more information, p... | false | 21,403 | false | yelp_polarity | 2022-11-03T16:47:20.000Z | null | false | 09666a5500278b7514340ec4747095de97080178 | [] | [
"arxiv:1509.01626",
"language:en"
] | https://huggingface.co/datasets/yelp_polarity/resolve/main/README.md | ---
language:
- en
paperswithcode_id: null
pretty_name: YelpPolarity
train-eval-index:
- config: plain_text
task: text-classification
task_id: binary_classification
splits:
train_split: train
eval_split: test
col_mapping:
text: text
label: target
metrics:
- type: accuracy
name: Accuracy
... |
null | null | @inproceedings{zhang2015character,
title={Character-level convolutional networks for text classification},
author={Zhang, Xiang and Zhao, Junbo and LeCun, Yann},
booktitle={Advances in neural information processing systems},
pages={649--657},
year={2015}
} | The Yelp reviews dataset consists of reviews from Yelp. It is extracted from the Yelp Dataset Challenge 2015 data.
The Yelp reviews full star dataset is constructed by Xiang Zhang (xiang.zhang@nyu.edu) from the above dataset.
It is first used as a text classification benchmark in the following paper: Xiang Zhang, Junbo... | false | 42,882 | false | yelp_review_full | 2022-11-03T16:47:32.000Z | null | false | c41606e91c57f9a35a046b0131533446e5ecda54 | [] | [
"arxiv:1509.01626",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language:en",
"license:other",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:sentiment-classification"
] | https://huggingface.co/datasets/yelp_review_full/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- other
license_details: yelp-licence
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
paperswithcode_id: ... |
null | null | @inproceedings{hedderich-etal-2020-transfer,
title = "Transfer Learning and Distant Supervision for Multilingual Transformer Models: A Study on African Languages",
author = "Hedderich, Michael A. and
Adelani, David and
Zhu, Dawei and
Alabi, Jesujoba and
Markus, Udia and
Klakow... | A collection of news article headlines in Yoruba from BBC Yoruba.
Each headline is labeled with one of the following classes: africa,
entertainment, health, nigeria, politics, sport or world.
The dataset was presented in the paper:
Hedderich, Adelani, Zhu, Alabi, Markus, Klakow: Transfer Learning and
Distant Supervisi... | false | 321 | false | yoruba_bbc_topics | 2022-11-03T16:08:05.000Z | null | false | af1c281bf1d2d6d4abc1c23c6281b6c8b507b8ee | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language:yo",
"license:unknown",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:topic-classification"
] | https://huggingface.co/datasets/yoruba_bbc_topics/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- yo
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- topic-classification
paperswithcode_id: null
pretty_name: Yoruba Bbc News To... |
null | null | @inproceedings{alabi-etal-2020-massive,
title = "Massive vs. Curated Embeddings for Low-Resourced Languages: the Case of {Yorùbá} and {T}wi",
author = "Alabi, Jesujoba and
Amponsah-Kaakyire, Kwabena and
Adelani, David and
Espa{\\~n}a-Bonet, Cristina",
booktitle = "Proceedings of the 12t... | The Yoruba GV NER dataset is a labeled dataset for named entity recognition in Yoruba. The texts were obtained from
Yoruba Global Voices News articles https://yo.globalvoices.org/ . We concentrate on
four types of named entities: persons [PER], locations [LOC], organizations [ORG], and dates & time [DATE].
The Yoruba ... | false | 319 | false | yoruba_gv_ner | 2022-11-03T16:08:06.000Z | null | false | 2c17f4680e52ab8232711152ae8eb98a7fa4a519 | [] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:yo",
"license:cc-by-3.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:token-classification",
"task_ids:named-entity-recognition"
] | https://huggingface.co/datasets/yoruba_gv_ner/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- yo
license:
- cc-by-3.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
paperswithcode_id: null
pretty_name: ... |
null | null | @inproceedings{alabi-etal-2020-massive,
title = "Massive vs. Curated Embeddings for Low-Resourced Languages: the Case of Yoruba and {T}wi",
author = "Alabi, Jesujoba and
Amponsah-Kaakyire, Kwabena and
Adelani, David and
Espa{\\~n}a-Bonet, Cristina",
booktitle = "Proceedings of the 12th ... | Yoruba Text C3 is the largest Yoruba texts collected and used to train FastText embeddings in the
YorubaTwi Embedding paper: https://www.aclweb.org/anthology/2020.lrec-1.335/ | false | 320 | false | yoruba_text_c3 | 2022-11-03T16:08:16.000Z | null | false | 48b5590484e2eef28eef0bded0a2537a9e564fd5 | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language:yo",
"license:cc-by-nc-4.0",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_i... | https://huggingface.co/datasets/yoruba_text_c3/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- yo
license:
- cc-by-nc-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
paperswithcode_id... |
null | null | @inproceedings{alabi-etal-2020-massive,
title = "Massive vs. Curated Embeddings for Low-Resourced Languages: the Case of {Y}or{\\`u}b{\\'a} and {T}wi",
author = "Alabi, Jesujoba and
Amponsah-Kaakyire, Kwabena and
Adelani, David and
Espa{\\~n}a-Bonet, Cristina",
booktitle = "Proceedings ... | A translation of the word pair similarity dataset wordsim-353 to Yorùbá.
The dataset was presented in the paper
Alabi et al.: Massive vs. Curated Embeddings for Low-Resourced
Languages: the Case of Yorùbá and Twi (LREC 2020). | false | 319 | false | yoruba_wordsim353 | 2022-11-03T16:07:49.000Z | null | false | 9d07d45ddc610cdead4658da2f39c18054977ca6 | [] | [
"annotations_creators:crowdsourced",
"language_creators:expert-generated",
"language:en",
"language:yo",
"license:unknown",
"multilinguality:multilingual",
"size_categories:n<1K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:text-scoring",
"task_ids:semantic-simil... | https://huggingface.co/datasets/yoruba_wordsim353/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- expert-generated
language:
- en
- yo
license:
- unknown
multilinguality:
- multilingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- text-scoring
- semantic-similarity-scoring
paperswithcode_id: null
... |
null | null | null | Dataset built from pairs of YouTube captions where both 'auto-generated' and
'manually-corrected' captions are available for a single specified language.
This dataset labels two-way (e.g. ignoring single-sided insertions) same-length
token differences in the `diff_type` column. The `default_seq` is composed of
tokens f... | false | 324 | false | youtube_caption_corrections | 2022-11-03T16:15:28.000Z | null | false | d39fe3f7856cbcbb34db9277f8c82aea6a5dc0a0 | [] | [
"annotations_creators:expert-generated",
"annotations_creators:machine-generated",
"language_creators:machine-generated",
"language:en",
"license:mit",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:other",
"task_categories:text-generation... | https://huggingface.co/datasets/youtube_caption_corrections/resolve/main/README.md | ---
annotations_creators:
- expert-generated
- machine-generated
language_creators:
- machine-generated
language:
- en
license:
- mit
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- other
- text-generation
- fill-mask
task_ids:
- slot-filling
paperswithcode_id... |
null | null | @inproceedings{weller-etal-2020-learning,
title = "Learning from Task Descriptions",
author = "Weller, Orion and
Lourie, Nicholas and
Gardner, Matt and
Peters, Matthew",
booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
mon... | ZEST tests whether NLP systems can perform unseen tasks in a zero-shot way, given a natural language description of
the task. It is an instantiation of our proposed framework "learning from task descriptions". The tasks include
classification, typed entity extraction and relationship extraction, and each task is paired... | false | 587 | false | zest | 2022-11-03T16:30:48.000Z | zest | false | 8b22ea68745f08a9e0b2ff7c83bb4190841ef49c | [] | [
"arxiv:2011.08115",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:question-answering",
"task_categories:token-classification",
"t... | https://huggingface.co/datasets/zest/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
- token-classification
task_ids:
- closed-domain-qa
- extractive-qa
paperswithcode... |
AI-Sweden | null | \ | \ | false | 2,043 | false | AI-Sweden/SuperLim | 2022-10-21T15:25:24.000Z | null | false | 7ebf0b4caa7b2ae39698a889de782c09e6f5ee56 | [] | [
"language:sv",
"multilinguality:monolingual",
"task_categories:question-answering",
"task_categories:text-classification",
"task_categories:other"
] | https://huggingface.co/datasets/AI-Sweden/SuperLim/resolve/main/README.md | ---
language:
- sv
multilinguality:
- monolingual
pretty_name: SuperLim
task_categories:
- question-answering
- text-classification
- sequence-modeling
- other
---
# Dataset Card for SuperLim
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summ... |
ARTeLab | null | null | null | false | 409 | false | ARTeLab/fanpage | 2022-07-01T15:35:47.000Z | null | false | c8fe14be8fa86f2324ba3fdf22e79e511e1c0147 | [] | [
"language:it",
"license:unknown",
"multilinguality:monolingual",
"size_categories:10K<n<100k",
"source_datasets:original",
"task_categories:summarization",
"task_ids:summarization"
] | https://huggingface.co/datasets/ARTeLab/fanpage/resolve/main/README.md | ---
language:
- it
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100k
source_datasets:
- original
task_categories:
- summarization
task_ids:
- summarization
---
# Dataset Card for fanpage
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-sum... |
ARTeLab | null | null | null | false | 468 | false | ARTeLab/ilpost | 2022-10-24T12:17:37.000Z | null | false | ce03533a711db7745d5ed507fbc579544ac50f39 | [] | [
"language:it",
"multilinguality:monolingual",
"size_categories:10K<n<100k",
"task_categories:summarization",
"task_ids:summarization"
] | https://huggingface.co/datasets/ARTeLab/ilpost/resolve/main/README.md | ---
language:
- it
multilinguality:
- monolingual
size_categories:
- 10K<n<100k
task_categories:
- summarization
task_ids:
- summarization
---
# Dataset Card for ilpost
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and... |
ARTeLab | null | null | null | false | 351 | false | ARTeLab/mlsum-it | 2022-10-24T12:26:44.000Z | null | false | 2c7096b9ac350baf13c424ca17ab0eb125c0b196 | [] | [
"language:it",
"multilinguality:monolingual",
"size_categories:10K<n<100k",
"task_categories:summarization",
"task_ids:summarization"
] | https://huggingface.co/datasets/ARTeLab/mlsum-it/resolve/main/README.md | ---
language:
- it
multilinguality:
- monolingual
size_categories:
- 10K<n<100k
task_categories:
- summarization
task_ids:
- summarization
---
# Dataset Card for mlsum-it
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-a... |
ASCCCCCCCC | null | null | null | false | 319 | false | ASCCCCCCCC/amazon_zh | 2022-02-17T02:16:59.000Z | null | false | f37c573d8d99bd0eff5c547282b990db5bc7a20e | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/ASCCCCCCCC/amazon_zh/resolve/main/README.md | ---
license: apache-2.0
---
this is a datasets about amazon reviews |
ASCCCCCCCC | null | null | null | false | 319 | false | ASCCCCCCCC/amazon_zh_simple | 2022-02-22T01:37:48.000Z | null | false | 14059f8980b8e8bc298293d160293d7ce6752c92 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/ASCCCCCCCC/amazon_zh_simple/resolve/main/README.md | ---
license: apache-2.0
---
|
Abdo1Kamr | null | null | null | false | 163 | false | Abdo1Kamr/Arabic_Hadith | 2021-08-21T12:40:44.000Z | null | false | 7af49f85461104c4e7172a55659d09ca423cd160 | [] | [] | https://huggingface.co/datasets/Abdo1Kamr/Arabic_Hadith/resolve/main/README.md | # Hadith-Data-Sets
There are two files of Hadith, the first one for all `hadith With Tashkil and Without Tashkel` from the Nine Books that are 62,169 Hadith.
The second one it `Hadith pre-processing` data, which is applyed normalization and removeing stop words and lemmatization on it
<!-- ## `All Hadith Books`: All Ha... |
Abirate | null | null | null | false | 346 | false | Abirate/english_quotes | 2022-10-25T08:39:16.000Z | null | false | 7b544c4920a8be268b48b403c188acf0a462051b | [] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language_creators:crowdsourced",
"language:en",
"multilinguality:monolingual",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:multi-label-classification"
] | https://huggingface.co/datasets/Abirate/english_quotes/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
- crowdsourced
language:
- en
multilinguality:
- monolingual
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-label-classification
---
# ****Dataset Card for English quotes****
# **I-Dataset Summary*... |
Abirate | null | null | null | false | 325 | false | Abirate/french_book_reviews | 2022-08-25T19:26:48.000Z | null | false | 534725e03fec6f560dbe8166e8ae3825314a6290 | [] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language_creators:crowdsourced",
"language:fr",
"multilinguality:monolingual",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:multi-label-classification"
] | https://huggingface.co/datasets/Abirate/french_book_reviews/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
- crowdsourced
language:
- fr
multilinguality:
- monolingual
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-label-classification
---
# ****Dataset Card for French book reviews****
# **I-Dataset Sum... |
AhmedSSoliman | null | null | null | false | 580 | false | AhmedSSoliman/CoNaLa | 2022-01-22T09:34:19.000Z | null | false | 08ecce2f116f895feb3f2a5a5b7beeef761ea68f | [] | [] | https://huggingface.co/datasets/AhmedSSoliman/CoNaLa/resolve/main/README.md | ---
task_categories:
- Code Generation
- Translation
- Text2Text generation
---
# CoNaLa Dataset for Code Generation
## Table of content
- [Dataset Description](#dataset-description)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fi... |
Aisha | null | null | null | false | 321 | false | Aisha/BAAD16 | 2022-10-22T05:31:54.000Z | null | false | 532717d4f35316fe8b8eef21d07f9cf12c4ab537 | [] | [
"arxiv:2001.05316",
"annotations_creators:found",
"annotations_creators:crowdsourced",
"annotations_creators:expert-generated",
"language_creators:found",
"language_creators:crowdsourced",
"language:bn",
"license:cc-by-4.0",
"multilinguality:monolingual",
"source_datasets:original",
"task_catego... | https://huggingface.co/datasets/Aisha/BAAD16/resolve/main/README.md | ---
annotations_creators:
- found
- crowdsourced
- expert-generated
language_creators:
- found
- crowdsourced
language:
- bn
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: 'BAAD16: Bangla Authorship Attribution Dataset (16 Authors)'
source_datasets:
- original
task_categories:
- text-classification
ta... |
Aisha | null | null | null | false | 321 | false | Aisha/BAAD6 | 2022-10-22T05:30:28.000Z | null | false | 962505e1575d4c2f04745c1c1e906e9eeebeec03 | [] | [
"annotations_creators:found",
"annotations_creators:crowdsourced",
"annotations_creators:expert-generated",
"language_creators:found",
"language_creators:crowdsourced",
"language:bn",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"task... | https://huggingface.co/datasets/Aisha/BAAD6/resolve/main/README.md | ---
annotations_creators:
- found
- crowdsourced
- expert-generated
language_creators:
- found
- crowdsourced
language:
- bn
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: 'BAAD6: Bangla Authorship Attribution Dataset (6 Authors)'
size_categories:
- unknown
source_datasets:
- original
task_categories:... |
Akshith | null | null | null | false | 322 | false | Akshith/test | 2021-05-14T15:43:13.000Z | null | false | 862dd7d22ac5f6a035aeb743f3a7cec9df0da6ec | [] | [] | https://huggingface.co/datasets/Akshith/test/resolve/main/README.md | |
AlexZapolskii | null | null | null | false | 320 | false | AlexZapolskii/zapolskii-amazon | 2021-12-22T22:13:57.000Z | null | false | 9fda7cad48bcda0c9f95c4e2e72c2966671f3f04 | [] | [] | https://huggingface.co/datasets/AlexZapolskii/zapolskii-amazon/resolve/main/README.md | dataset from kaggle https://www.kaggle.com/c/amazon-pet-product-reviews-classification |
AlgoveraAI | null | null | CryptoPunks is a non-fungible token (NFT) collection on the Ethereum blockchain. The dataset contains 10,000 CryptoPunk images, most of humans but also of three special types: Zombie (88), Ape (24) and Alien (9). They are provided with both clear backgrounds and teal backgrounds. | false | 166 | false | AlgoveraAI/CryptoPunks | 2022-02-28T15:25:44.000Z | null | false | c31fe59b441510cba533513a8d35b0d0126d1ced | [] | [] | https://huggingface.co/datasets/AlgoveraAI/CryptoPunks/resolve/main/README.md | # Dataset Card for CIFAR-10
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Dataset Structure](#dataset-structure)
- [Data Fields](#data-fields)
- [Additional Information](#additional-information)
- [Ocean Protocol](#ocean-protocol)
- [Algovera](#algo... |
Alvenir | null | null | null | false | 318 | false | Alvenir/nst-da-16khz | 2021-11-29T08:58:25.000Z | null | false | 758333c328d446c1f24ce93320a60feecac3bc72 | [] | [] | https://huggingface.co/datasets/Alvenir/nst-da-16khz/resolve/main/README.md | # NST Danish 16kHz dataset from Sprakbanken
Data is from sprakbanken and can be accessed using following [link](https://www.nb.no/sprakbanken/en/resource-catalogue/oai-nb-no-sbr-19/).
|
Arnold | null | null | null | false | 322 | false | Arnold/hausa_common_voice | 2022-02-10T03:28:22.000Z | null | false | a851e86f3029526f5e239beff1da3130fa9802f7 | [] | [] | https://huggingface.co/datasets/Arnold/hausa_common_voice/resolve/main/README.md | This dataset is from the common voice corpus 7.0 using the Hausa dataset |
AryanLala | null | null | null | false | 322 | false | AryanLala/autonlp-data-Scientific_Title_Generator | 2021-11-20T18:00:56.000Z | null | false | 704cf00070272d949d97d8688f81809e95ed23d9 | [] | [] | https://huggingface.co/datasets/AryanLala/autonlp-data-Scientific_Title_Generator/resolve/main/README.md | ---
task_categories:
- conditional-text-generation
---
# AutoNLP Dataset for project: Scientific_Title_Generator
## Table of content
- [Dataset Description](#dataset-description)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-field... |
Atsushi | null | null | null | false | 332 | false | Atsushi/fungi_diagnostic_chars_comparison_japanese | 2022-11-05T12:19:10.000Z | null | false | af5b9316617c0ed71200d0906d001d27843d30a4 | [] | [
"annotations_creators:other",
"language:ja",
"license:cc-by-4.0",
"multilinguality:monolingual",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:multi-class-classification",
"size_categories:100K<n<1M"
] | https://huggingface.co/datasets/Atsushi/fungi_diagnostic_chars_comparison_japanese/resolve/main/README.md | ---
annotations_creators:
- other
language:
- ja
license:
- cc-by-4.0
multilinguality:
- monolingual
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-class-classification
size_categories:
- 100K<n<1M
---
fungi_diagnostic_chars_comparison_japanese
大菌輪「識別形質まとめ」データセット
最終更新日：2022/11... |
Atsushi | null | null | null | false | 323 | false | Atsushi/fungi_indexed_mycological_papers_japanese | 2022-11-05T12:21:15.000Z | null | false | 34ced2a4a782932f5c5d660adf8a7e0e908ff652 | [] | [
"annotations_creators:other",
"language:ja",
"license:cc-by-4.0",
"multilinguality:monolingual",
"source_datasets:original",
"size_categories:1K<n<10K"
] | https://huggingface.co/datasets/Atsushi/fungi_indexed_mycological_papers_japanese/resolve/main/README.md | ---
annotations_creators:
- other
language:
- ja
license:
- cc-by-4.0
multilinguality:
- monolingual
source_datasets:
- original
size_categories:
- 1K<n<10K
---
fungi_indexed_mycological_papers_japanese
大菌輪「論文3行まとめ」データセット
最終更新日：2022/11/5（R3-10032まで）
====
### Languages
Japanese
This dataset is available in Japa... |
Atsushi | null | null | null | false | 323 | false | Atsushi/fungi_trait_circus_database | 2022-08-13T07:42:33.000Z | null | false | 5c9e513083cf5c97734c58db85236bd6b01172b8 | [] | [
"annotations_creators:other",
"language:en",
"language:ja",
"multilinguality:multilingual",
"license:cc-by-4.0",
"source_datasets:original",
"size_categories:100K<n<1M"
] | https://huggingface.co/datasets/Atsushi/fungi_trait_circus_database/resolve/main/README.md | ---
annotations_creators:
- other
language:
- en
- ja
multilinguality:
- multilingual
license:
- cc-by-4.0
source_datasets:
- original
size_categories:
- 100K<n<1M
---
fungi_trait_circus_database
大菌輪「Trait Circus」データセット（統制形質）
最終更新日：2022/8/13
====
### Languages
Japanese and English
Please do not use this datas... |
BSC-TeMU | null | bibtex
@article{DBLP:journals/corr/abs-2107-07253,
author = {Asier Guti{\'{e}}rrez{-}Fandi{\~{n}}o and
Jordi Armengol{-}Estap{\'{e}} and
Marc P{\`{a}}mies and
Joan Llop{-}Palao and
Joaqu{\'{\i}}n Silveira{-}Ocampo and
Casimiro Pio Carrino a... | This dataset contains 6,247 contexts and 18,817 questions with their answers, 1 to 5 for each fragment.
The sources of the contexts are:
* Encyclopedic articles from [Wikipedia in Spanish](https://es.wikipedia.org/), used under [CC-by-sa licence](https://creativecommons.org/licenses/by-sa/3.0/legalcode).
* News fro... | false | 323 | false | BSC-TeMU/SQAC | 2022-07-01T15:31:18.000Z | null | false | d00a3d8ba5e469a54ea7a3ddf52aebc7faf22e65 | [] | [
"arxiv:2107.07253",
"arxiv:1606.05250",
"annotations_creators:expert-generated",
"language_creators:found",
"language:es",
"license:cc-by-sa-4.0",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"task_categories:question-answering",
"task_ids:extractive-qa"
... | https://huggingface.co/datasets/BSC-TeMU/SQAC/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- es
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: Spanish Question Answering Corpus (SQAC)
size_categories:
- unknown
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractive-qa
---
... |
BSC-TeMU | null | AnCora Catalan NER.
This is a dataset for Named Eentity Reacognition (NER) from Ancora corpus adapted for
Machine Learning and Language Model evaluation purposes.
Since multiwords (including Named Entites) in the original Ancora corpus are aggregated as
... | false | 320 | false | BSC-TeMU/ancora-ca-ner | 2022-10-25T08:39:42.000Z | null | false | 7f39eb2602fbcf4112a211ee76471df9fc8f3efe | [] | [
"language:ca"
] | https://huggingface.co/datasets/BSC-TeMU/ancora-ca-ner/resolve/main/README.md | ---
language:
- ca
---
# Named Entites from Ancora Corpus
## BibTeX citation
If you use any of these resources (datasets or models) in your work, please cite our latest paper:
```bibtex
@inproceedings{armengol-estape-etal-2021-multilingual,
title = "Are Multilingual Models the Best Choice for Moderately Under-... | |
BSC-TeMU | null | Rodriguez-Penagos, Carlos Gerardo, Armentano-Oller, Carme, Gonzalez-Agirre, Aitor, & Gibert Bonet, Ona. (2021).
Semantic Textual Similarity in Catalan (Version 1.0.1) [Data set].
Zenodo. http://doi.org/10.5281/zenodo.4761434 | Semantic Textual Similarity in Catalan.
STS corpus is a benchmark for evaluating Semantic Text Similarity in Catalan.
It consists of more than 3000 sentence pairs, annotated with the semantic similarity between them,
using a scale from 0 (no similarity at all) to 5... | false | 321 | false | BSC-TeMU/sts-ca | 2022-10-25T08:40:44.000Z | null | false | 1617848affcbd0b6ae9d65c33dd0c7783b616713 | [] | [
"language:ca"
] | https://huggingface.co/datasets/BSC-TeMU/sts-ca/resolve/main/README.md | ---
language:
- ca
---
# Semantic Textual Similarity in Catalan
## BibTeX citation
If you use any of these resources (datasets or models) in your work, please cite our latest paper:
```bibtex
@inproceedings{armengol-estape-etal-2021-multilingual,
title = "Are Multilingual Models the Best Choice for Moderately U... |
BSC-TeMU | null | Carrino, Casimiro Pio, Rodriguez-Penagos, Carlos Gerardo, & Armentano-Oller, Carme. (2021).
TeCla: Text Classification Catalan dataset (Version 1.0) [Data set].
Zenodo. http://doi.org/10.5281/zenodo.4627198 | TeCla: Text Classification Catalan dataset
Catalan News corpus for Text classification, crawled from ACN (Catalan News Agency) site: www.acn.cat
Corpus de notícies en català per a classificació textual, extret del web de l'Agència Catalana de Notícies - www.acn.cat | false | 321 | false | BSC-TeMU/tecla | 2022-10-25T08:40:52.000Z | null | false | 102a47e295036d09dd75afd61618d6755484eee2 | [] | [
"language:ca"
] | https://huggingface.co/datasets/BSC-TeMU/tecla/resolve/main/README.md | ---
language:
- ca
---
# TeCla (Text Classification) Catalan dataset
## BibTeX citation
If you use any of these resources (datasets or models) in your work, please cite our latest paper:
```bibtex
@inproceedings{armengol-estape-etal-2021-multilingual,
title = "Are Multilingual Models the Best Choice for Moderat... |
BSC-TeMU | null | Rodriguez-Penagos, Carlos Gerardo, & Armentano-Oller, Carme. (2021).
ViquiQuAD: an extractive QA dataset from Catalan Wikipedia (Version ViquiQuad_v.1.0.1)
[Data set]. Zenodo. http://doi.org/10.5281/zenodo.4761412 | ViquiQuAD: an extractive QA dataset from Catalan Wikipedia.
This dataset contains 3111 contexts extracted from a set of 597 high quality original (no translations)
articles in the Catalan Wikipedia "Viquipèdia" (ca.wikipedia.org), and 1 to 5 questions with their
an... | false | 322 | false | BSC-TeMU/viquiquad | 2022-10-25T08:40:59.000Z | null | false | 54f58ea7d1e8efc42142dfd0487a1b8210c3af09 | [] | [
"arxiv:1606.05250",
"language:ca"
] | https://huggingface.co/datasets/BSC-TeMU/viquiquad/resolve/main/README.md | ---
language:
- ca
---
# ViquiQuAD, An extractive QA dataset for catalan, from the Wikipedia
## BibTeX citation
If you use any of these resources (datasets or models) in your work, please cite our latest paper:
```bibtex
@inproceedings{armengol-estape-etal-2021-multilingual,
title = "Are Multilingual Models the... |
BSC-TeMU | null | Carlos Gerardo Rodriguez-Penagos, & Carme Armentano-Oller. (2021). XQuAD-ca [Data set].
Zenodo. http://doi.org/10.5281/zenodo.4757559 | Professional translation into Catalan of XQuAD dataset (https://github.com/deepmind/xquad).
XQuAD (Cross-lingual Question Answering Dataset) is a benchmark dataset for evaluating
cross-lingual question answering performance.
The dataset consists of a subset of 240... | false | 321 | false | BSC-TeMU/xquad-ca | 2022-10-25T08:41:16.000Z | null | false | 9bd7489b3bf4f809c16f3eba2f3b75c7dbc34b2f | [] | [
"arxiv:1910.11856",
"language:ca"
] | https://huggingface.co/datasets/BSC-TeMU/xquad-ca/resolve/main/README.md | ---
language:
- ca
---
# XQuAD-Ca
## BibTeX citation
If you use any of these resources (datasets or models) in your work, please cite our latest paper:
```bibtex
@inproceedings{armengol-estape-etal-2021-multilingual,
title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} ... |
Babelscape | null | @inproceedings{huguet-cabot-navigli-2021-rebel,
title = "REBEL: Relation Extraction By End-to-end Language generation",
author = "Huguet Cabot, Pere-Llu{\'\i}s and
Navigli, Roberto",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2021",
month = nov,
year = "... | REBEL is a silver dataset created for the paper REBEL: Relation Extraction By End-to-end Language generation | false | 340 | false | Babelscape/rebel-dataset | 2022-10-25T08:25:46.000Z | null | false | dcd6511ccda65398f44a2ba41b9276583b98254f | [] | [
"arxiv:2005.00614",
"annotations_creators:machine-generated",
"language_creators:machine-generated",
"language:en",
"license:cc-by-nc-sa-4.0",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"task_categories:text-retrieval",
"task_categories:text-generation",
... | https://huggingface.co/datasets/Babelscape/rebel-dataset/resolve/main/README.md | ---
annotations_creators:
- machine-generated
language_creators:
- machine-generated
language:
- en
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets:
- original
task_categories:
- text-retrieval
- text-generation
task_ids: []
pretty_name: rebel-dataset
tags:
- relatio... |
Babelscape | null | null | null | false | 2,339 | false | Babelscape/wikineural | 2022-11-13T07:52:46.000Z | null | false | 74c9b9dca034bb1606a6769457983904bd976803 | [] | [
"arxiv:1810.04805",
"annotations_creators:machine-generated",
"language_creators:machine-generated",
"language:de",
"language:en",
"language:es",
"language:fr",
"language:it",
"language:nl",
"language:pl",
"language:pt",
"language:ru",
"license:cc-by-nc-sa-4.0",
"multilinguality:multilingu... | https://huggingface.co/datasets/Babelscape/wikineural/resolve/main/README.md | ---
annotations_creators:
- machine-generated
language_creators:
- machine-generated
language:
- de
- en
- es
- fr
- it
- nl
- pl
- pt
- ru
license:
- cc-by-nc-sa-4.0
multilinguality:
- multilingual
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: wik... |
Baybars | null | null | null | false | 317 | false | Baybars/parla_text_corpus | 2022-10-21T15:29:15.000Z | null | false | a388264362bb51412653f3da7b18f37fd24fab30 | [] | [
"annotations_creators:no-annotation",
"language_creators:various",
"language:ca",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:100k<n<1M",
"source_datasets:found",
"task_ids:language-modeling",
"tags:robust-speech-event"
] | https://huggingface.co/datasets/Baybars/parla_text_corpus/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- various
language:
- ca
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: ParlaTextCorpus
size_categories:
- 100k<n<1M
source_datasets:
- found
task_categories:
- sequence-modeling
task_ids:
- language-modeling
tags:
- robust-speech-event
---
... |
BeIR | null | null | null | false | 472 | false | BeIR/beir-corpus | 2022-10-21T15:30:07.000Z | beir | false | 31cce8af65eb851c49dca96b280b957a6e745424 | [] | [
"language:en",
"license:cc-by-sa-4.0",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"size_categories:100k<n<1M",
"size_categories:1K<n<10K",
"size_categories:10K<n<100K",
"size_categories:100K<n<1M",
"task_categories:text-retrieval",
"task_ids:passage-retrieval",
"task_ids:entity-l... | https://huggingface.co/datasets/BeIR/beir-corpus/resolve/main/README.md | ---
annotations_creators: []
language_creators: []
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
paperswithcode_id: beir
pretty_name: BEIR Benchmark
size_categories:
msmarco:
- 1M<n<10M
trec-covid:
- 100k<n<1M
nfcorpus:
- 1K<n<10K
nq:
- 1M<n<10M
hotpotqa:
- 1M<n<10M
fiqa:
... |
BeIR | null | null | null | false | 642 | false | BeIR/beir | 2022-10-21T15:30:43.000Z | beir | false | 78edba255941a9f67828b606e79a08e497c9298f | [] | [
"language:en",
"license:cc-by-sa-4.0",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"size_categories:100k<n<1M",
"size_categories:1K<n<10K",
"size_categories:10K<n<100K",
"size_categories:100K<n<1M",
"task_categories:text-retrieval",
"task_ids:passage-retrieval",
"task_ids:entity-l... | https://huggingface.co/datasets/BeIR/beir/resolve/main/README.md | ---
annotations_creators: []
language_creators: []
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
paperswithcode_id: beir
pretty_name: BEIR Benchmark
size_categories:
msmarco:
- 1M<n<10M
trec-covid:
- 100k<n<1M
nfcorpus:
- 1K<n<10K
nq:
- 1M<n<10M
hotpotqa:
- 1M<n<10M
fiqa:
... |
Lacito | null | null | These datasets are extracts from the Pangloss collection and have
been preprocessed for ASR experiments in Na and Japhug. | false | 318 | false | Lacito/pangloss | 2022-09-06T18:02:34.000Z | null | false | f80e65ea3922bfab04afe8f4a07a8ab16bd81553 | [] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:jya",
"language:nru",
"language_bcp47:x-japh1234",
"language_bcp47:x-yong1288",
"language_details:jya consists of japh1234 (Glottolog code); nru consists of yong1288 (Glottolog code)",
"license:cc-by-nc-sa-4.0",
... | https://huggingface.co/datasets/Lacito/pangloss/resolve/main/README.md | ---
pretty_name: Pangloss
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- jya
- nru
language_bcp47:
- x-japh1234
- x-yong1288
language_details: jya consists of japh1234 (Glottolog code); nru consists of yong1288 (Glottolog code)
license: cc-by-nc-sa-4.0
multilinguality:
- mult... |
BritishLibraryLabs | null | \
@misc{british library_genre,
title={UK Doctoral Thesis Metadata from EThOS},
url={UK Doctoral Thesis Metadata from EThOS},
author={{British Library} and {Rosie, Heather}},
year={2021}} | The data in this collection comprises the bibliographic metadata for all UK doctoral theses listed in EThOS, the UK's national thesis service.
We estimate the data covers around 98% of all PhDs ever awarded by UK Higher Education institutions, dating back to 1787.
Thesis metadata from every PhD-awarding university in t... | false | 471 | false | BritishLibraryLabs/EThOS-PhD-metadata | 2022-07-23T21:14:57.000Z | null | false | 66bfd05a6720c6eb0d274779cec9b0632622c682 | [] | [
"language:en",
"multilinguality:monolingual",
"task_categories:text-classification",
"task_categories:fill-mask",
"task_ids:multi-label-classification",
"task_ids:masked-language-modeling"
] | https://huggingface.co/datasets/BritishLibraryLabs/EThOS-PhD-metadata/resolve/main/README.md | ---
annotations_creators: []
language:
- en
language_creators: []
license: []
multilinguality:
- monolingual
pretty_name: EThOS PhD metadata
size_categories: []
source_datasets: []
tags: []
task_categories:
- text-classification
- fill-mask
task_ids:
- multi-label-classification
- masked-language-modeling
---
# Datase... |
CAGER | null | null | null | false | 164 | false | CAGER/rick | 2021-07-09T02:05:44.000Z | null | false | f002ce337df0b0f1fb96f87edd17b2ebe4a73963 | [] | [] | https://huggingface.co/datasets/CAGER/rick/resolve/main/README.md | welcoe to cager data set |
CALM | null | null | null | false | 316 | false | CALM/arwiki | 2022-08-01T16:37:23.000Z | null | false | 36dcd9cf86cfc635866ec63d58ef5ee25885ac4d | [] | [
"language:ar",
"license:unknown",
"multilinguality:monolingual"
] | https://huggingface.co/datasets/CALM/arwiki/resolve/main/README.md | ---
pretty_name: Wikipedia Arabic dumps dataset.
language:
- ar
license:
- unknown
multilinguality:
- monolingual
---
# Arabic Wiki Dataset
## Dataset Summary
This dataset is extracted using [`wikiextractor`](https://github.com/attardi/wikiextractor) tool, from [Wikipedia Arabic pages](https://dumps.wikimedia.org/arw... |
CAiRE | null | @inproceedings{lovenia2021ascend,
title = {ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation},
author = {Lovenia, Holy and Cahyawijaya, Samuel and Winata, Genta Indra and Xu, Peng and Yan, Xu and Liu, Zihan and Frieske, Rita and Yu, Tiezheng and Dai, Wenliang and Bar... | ASCEND (A Spontaneous Chinese-English Dataset) introduces a high-quality resource of spontaneous multi-turn conversational dialogue Chinese-English code-switching corpus collected in Hong Kong. ASCEND consists of 10.62 hours of spontaneous speech with a total of ~12.3K utterances. The corpus is split into 3 sets: train... | false | 676 | false | CAiRE/ASCEND | 2022-10-24T12:43:58.000Z | null | false | b966160952fc5fe9cb036f098dd44f135d5c6f20 | [] | [
"arxiv:2112.06223",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"language:en",
"language:zh",
"license:cc-by-sa-4.0",
"multilinguality:multilingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:automatic-speech-recognition",
"tags:spe... | https://huggingface.co/datasets/CAiRE/ASCEND/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
language:
- en
- zh
license:
- cc-by-sa-4.0
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- automatic-speech-recognition
task_ids: []
pretty_name: 'ASCEND: A Spontaneous Chinese-En... |
CShorten | null | null | null | false | 165 | false | CShorten/KerasBERT | 2022-06-28T11:51:07.000Z | null | false | 563ad7cd6591c8a51a807ce073645e349ce92fa8 | [] | [] | https://huggingface.co/datasets/CShorten/KerasBERT/resolve/main/README.md | <h1>KerasBERT</h1>
<ul>
<li>All Data</li>
<li>Keras API Docs</li>
<li>Keras Developer Guides</li>
<li>Keras Code Examples</li>
</ul>
Please cite KerasBERT: Modeling the Keras Language, Connor Shorten and Taghi M. Khoshgoftaar. https://ieeexplore.ieee.org/abstract/document/9679980. |
Champion | null | null | null | false | 166 | false | Champion/vpc2020_clear_anon_speech | 2021-10-12T14:19:45.000Z | null | false | d0be437cfd0d5d653ffd582514f55cb1f039ba16 | [] | [] | https://huggingface.co/datasets/Champion/vpc2020_clear_anon_speech/resolve/main/README.md | Repo to share original and anonymized speech of vpc2020
|
Cheranga | null | null | null | false | 162 | false | Cheranga/test | 2022-02-10T01:34:34.000Z | null | false | 0267de0892db58df76ab0ba08d07debeceb55aff | [] | [
"license:afl-3.0"
] | https://huggingface.co/datasets/Cheranga/test/resolve/main/README.md | ---
license: afl-3.0
---
|
Chun | null | null | null | false | 318 | false | Chun/dataset | 2021-08-24T08:16:33.000Z | null | false | f496e251dd03afb88f8a19b8bdb47b6ae41a2408 | [] | [] | https://huggingface.co/datasets/Chun/dataset/resolve/main/README.md | A translation dataset between english and traditional chinese
train : 101497 rows
val : 1000 rows
test : 1000 rows
|
CodedotAI | null | @misc{cooper-2021-code-clippy-data,
author = {Nathan Coooper, Artashes Arutiunian, Santiago Hincapié-Potes, Ben Trevett, Arun Raja, Erfan Hossami, Mrinal Mathur, and contributors},
title = {{Code Clippy Data: A large dataset of code data from Github for research into code language models}},
mon... | This dataset was generated by selecting GitHub repositories from a large collection of repositories. These repositories were collected from https://seart-ghs.si.usi.ch/ and Github portion of [The Pile](https://github.com/EleutherAI/github-downloader) (performed on July 7th, 2021). The goal of this dataset is to provide... | false | 164 | false | CodedotAI/code_clippy | 2022-07-01T15:32:00.000Z | null | false | 9ab49d63034bf74a84769df261fea528f079440f | [] | [
"arxiv:2107.03374",
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"language:code",
"license:gpl-3.0",
"multilinguality:multilingual",
"size_categories:unknown",
"source_datasets:original",
"task_ids:language-modeling"
] | https://huggingface.co/datasets/CodedotAI/code_clippy/resolve/main/README.md | ---
YAML tags:
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- code
license:
- gpl-3.0
multilinguality:
- multilingual
pretty_name: Code Clippy
size_categories:
- unknown
source_datasets:
- original
task_categories:
- sequence-modeling
task_ids:
- language-modeling
---
# Dataset Car... |
CodedotAI | null | null | The Code Clippy dataset consists of various public codebases from GitHub in 22 programming languages with 23 extensions totalling about 16 TB of data when uncompressed. The dataset was created from the public GitHub dataset on Google BiqQuery. | false | 165 | false | CodedotAI/code_clippy_github | 2022-08-05T02:57:36.000Z | null | false | cf9f33dec640f45228f8f3f5e6a7899a37f5f83e | [] | [
"arxiv:2107.03374",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"language:code",
"license:mit",
"multilinguality:multilingual",
"size_categories:unknown",
"task_ids:language-modeling"
] | https://huggingface.co/datasets/CodedotAI/code_clippy_github/resolve/main/README.md | ---
annotations_creators: []
language_creators:
- crowdsourced
- expert-generated
language: ["code"]
license:
- mit
multilinguality:
- multilingual
pretty_name: code-clippy-github-code
size_categories:
- unknown
source_datasets: []
task_categories:
- sequence-modeling
task_ids:
- language-modeling
---
# Code Clippy Git... |
Cropinky | null | null | null | false | 163 | false | Cropinky/flatearther | 2021-06-30T22:37:54.000Z | null | false | 41d4a7c0dceb496a6a7441a80bb28e430cae670e | [] | [] | https://huggingface.co/datasets/Cropinky/flatearther/resolve/main/README.md | ## Wow fishing bobber object detection dataset
Hello, here you will find a link to a csv i scraped using the scraper found at the same link. it contains paragraphs of text found on a flat earth conspiracy website
#TODO: turn it into an actualy huggingface dataset) |
Cropinky | null | null | null | false | 324 | false | Cropinky/rap_lyrics_english | 2021-07-21T03:07:36.000Z | null | false | 63ce731b2049c2d02e1c47a3ef15400c7e08d2e5 | [] | [] | https://huggingface.co/datasets/Cropinky/rap_lyrics_english/resolve/main/README.md | ## Rap lyrics dataset
this is the repo containing the dataset we made for the hugging face community week, in order to download more songs you need to request and get(it's very simple and fast) your genius API key which ou put in the genius.py file<br/>
#TODO: turn it into an actual huggingface dataset |
Cropinky | null | null | null | false | 320 | false | Cropinky/wow_fishing_bobber | 2021-06-30T22:14:04.000Z | null | false | 49a1de0829240746a613c3e9a6d7a98e6527827f | [] | [] | https://huggingface.co/datasets/Cropinky/wow_fishing_bobber/resolve/main/README.md | ## Wow fishing bobber object detection dataset
Hello, in this zip you will find 160 annotated images each containing 1 fishing bobber from World of warcraft.
I think this is an easy object detection datset, my yolov3 network was trained on it for 2000 iterations, it achieved
a loss of 0.05. It was working flawlessly as... |
Cyberfish | null | null | null | false | 321 | false | Cyberfish/pos_tagger | 2021-08-20T02:32:01.000Z | null | false | 81c2d1f3fc945fbc417173ce18aadf781efecd53 | [] | [] | https://huggingface.co/datasets/Cyberfish/pos_tagger/resolve/main/README.md | 词性标注训练集 |
Cyberfish | null | null | null | false | 321 | false | Cyberfish/text_error_correction | 2021-08-19T13:07:16.000Z | null | false | 577a560fa4ee1bf8d32480eefa9e14f416022016 | [] | [] | https://huggingface.co/datasets/Cyberfish/text_error_correction/resolve/main/README.md | 文本纠错的相关数据 |
CyranoB | null | @inproceedings{mcauley2013hidden,
title={Hidden factors and hidden topics: understanding rating dimensions with review text},
author={McAuley, Julian and Leskovec, Jure},
booktitle={Proceedings of the 7th ACM conference on Recommender systems},
pages={165--172},
year={2013}
} | The Amazon reviews dataset consists of reviews from amazon.
The data span a period of 18 years, including ~35 million reviews up to March 2013.
Reviews include product and user information, ratings, and a plaintext review. | false | 321 | false | CyranoB/polarity | 2022-10-25T08:54:09.000Z | null | false | 7582bab94af11d09843132c0aa36571f148fa304 | [] | [
"arxiv:1509.01626",
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"source_datasets:original",
"task_categories:text-classification",
"task_ids:sentiment-classification"
] | https://huggingface.co/datasets/CyranoB/polarity/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
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license:
- apache-2.0
multilinguality:
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size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
pretty_name: Amazon Review Polarity
---
# Da... |
DDSC | null | null | null | false | 641 | false | DDSC/angry-tweets | 2022-07-01T15:41:21.000Z | null | false | ba34e735abf46abc1e5d2675ac5c10e3fb9ff810 | [] | [
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"task_categories:text-classification",
"task_ids:sentiment-classification"
] | https://huggingface.co/datasets/DDSC/angry-tweets/resolve/main/README.md | ---
annotations_creators:
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language:
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license:
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multilinguality:
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pretty_name: AngryTweets
size_categories:
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source_datasets:
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task_categories:
- text-classification
task_ids:
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---
# Dataset Card for DKHa... |
DDSC | null | null | null | false | 321 | false | DDSC/europarl | 2022-07-01T15:42:03.000Z | null | false | 705be67c4566ea3ae65476b5a9fa44361d3a2287 | [] | [
"annotations_creators:expert-generated",
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"language:da",
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"source_datasets:original",
"task_categories:text-classification",
"task_ids:sentiment-classification"
] | https://huggingface.co/datasets/DDSC/europarl/resolve/main/README.md | ---
annotations_creators:
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language_creators:
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language:
- da
license:
- cc-by-4.0
multilinguality:
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pretty_name: TwitterSent
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
---
# Dataset Card for DKHa... |
DDSC | null | null | null | false | 422 | false | DDSC/lcc | 2022-07-01T15:44:15.000Z | null | false | 8cee426aac311cb33517ce16a2ccd79e90a7f299 | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language:da",
"license:cc-by-4.0",
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"source_datasets:original",
"task_categories:text-classification",
"task_ids:sentiment-classification"
] | https://huggingface.co/datasets/DDSC/lcc/resolve/main/README.md | ---
annotations_creators:
- expert-generated
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language:
- da
license:
- cc-by-4.0
multilinguality:
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pretty_name: TwitterSent
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
---
# Dataset Card for DKHa... |
DDSC | null | null | null | false | 321 | false | DDSC/partial-danish-gigaword-no-twitter | 2022-10-22T18:33:33.000Z | null | false | 2c176093ded85bbd5c35d52547461ac18d99cb28 | [] | [
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"language:da",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"task_categories:text-generation",
"task_ids:language-modeling",
"language_bcp47:da",
"language_bcp47:... | https://huggingface.co/datasets/DDSC/partial-danish-gigaword-no-twitter/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- da
license:
- cc-by-4.0
multilinguality:
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size_categories:
- unknown
source_datasets:
- original
task_categories:
- text-generation
task_ids:
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pretty_name: Danish Gigaword Corpus (no Twitter)
language... |
DDSC | null | null | null | false | 320 | false | DDSC/reddit-da | 2022-10-27T11:00:42.000Z | null | false | bc1302039dd6176aa5ce42342a25549c36587dc8 | [] | [
"annotations_creators:no-annotation",
"language_creators:found",
"language:da",
"license:mit",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"task_categories:text-generation",
"task_ids:language-modeling"
] | https://huggingface.co/datasets/DDSC/reddit-da/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- da
license:
- mit
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- text-generation
task_ids:
- language-modeling
pretty_name: Reddit-da
---
# Dataset Card for SQuAD-da
## Table of ... |
DDSC | null | null | null | false | 447 | false | DDSC/twitter-sent | 2022-07-01T15:44:26.000Z | null | false | 589ba98416d19168b59c26f992b4337815e55964 | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language:da",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:sentiment-classification"
] | https://huggingface.co/datasets/DDSC/twitter-sent/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- da
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: TwitterSent
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
---
# Dataset Card for ... |
DanL | null | null | null | false | 322 | false | DanL/scientific-challenges-and-directions-dataset | 2022-10-25T08:56:00.000Z | null | false | 4ed6a771c6c5b38cb2c4e84b11fc04646d0818fb | [] | [
"arxiv:2108.13751",
"arxiv:2004.10706",
"annotations_creators:expert-generated",
"language:en",
"multilinguality:monolingual",
"source_datasets:CORD-19",
"task_categories:text-classification",
"task_ids:multi-label-classification"
] | https://huggingface.co/datasets/DanL/scientific-challenges-and-directions-dataset/resolve/main/README.md | ---
YAML tags:
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- expert-generated
language_creators: []
language:
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license: []
multilinguality:
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pretty_name: DanL/scientific-challenges-and-directions-dataset
source_datasets:
- CORD-19
task_categories:
- text-classification
task_ids:
- multi-label-classification
---
# Dataset C... |
Daniele | null | null | null | false | 320 | false | Daniele/dante-corpus | 2021-11-12T11:44:16.000Z | null | false | 107a08bf312451a432f6cd75ae38688b67f85646 | [] | [] | https://huggingface.co/datasets/Daniele/dante-corpus/resolve/main/README.md | ---
YAML tags:
- copy-paste the tags obtained with the online tagging app: https://huggingface.co/spaces/huggingface/datasets-tagging
---
# Dataset Card for [Dataset Name]
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summar... |
Datatang | null | null | null | false | 320 | false | Datatang/accented_english | 2022-06-24T09:46:06.000Z | null | false | 14f9a0538f8c6dac63864d66801fc285c3159393 | [] | [] | https://huggingface.co/datasets/Datatang/accented_english/resolve/main/README.md | ---
YAML tags:
- copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging
---
# Dataset Card for accented-english
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supporte... |
Datatang | null | null | null | false | 318 | false | Datatang/accented_mandarin | 2022-06-24T09:46:46.000Z | null | false | dbeb88563d80c9ad2896b8fc0a038f4db945192a | [] | [] | https://huggingface.co/datasets/Datatang/accented_mandarin/resolve/main/README.md | ---
YAML tags:
- copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging
---
# Dataset Card for accented_mandarin
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Support... |
Datatang | null | null | null | false | 319 | false | Datatang/chinese_dialect | 2022-06-24T09:46:30.000Z | null | false | a3b3cc3f712507776384bb76b1a891cada70c796 | [] | [] | https://huggingface.co/datasets/Datatang/chinese_dialect/resolve/main/README.md | ---
YAML tags:
- copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging
---
# Dataset Card for chinese_dialect
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported... |
Datatang | null | null | null | false | 318 | false | Datatang/mandarin_chinese | 2022-06-24T09:46:38.000Z | null | false | 14c08a5292003a506fb4355a47c9205cedfaa2a1 | [] | [] | https://huggingface.co/datasets/Datatang/mandarin_chinese/resolve/main/README.md | ---
YAML tags:
- copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging
---
# Dataset Card for mandarin_chinese
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supporte... |
Datatang | null | null | null | false | 319 | false | Datatang/mixed_speech_chinese_english | 2022-06-24T09:46:22.000Z | null | false | 760b607ca2e788bde9240ce76fc95576adea53c8 | [] | [] | https://huggingface.co/datasets/Datatang/mixed_speech_chinese_english/resolve/main/README.md | ---
YAML tags:
- copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging
---
# Dataset Card for mixed_speech_chinese_english
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
... |
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