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SMS Spam Dataset
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Hi :) I added this [SMS Spam Dataset](http://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection)
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add DFKI SmartData Corpus
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- **Name:** DFKI SmartData Corpus - **Description:** DFKI SmartData Corpus is a dataset of 2598 German-language documents which has been annotated with fine-grained geo-entities, such as streets, stops and routes, as well as standard named entity types. - **Paper:** https://www.dfki.de/fileadmin/user_upload/import/9427_lrec_smartdata_corpus.pdf - **Data:** https://github.com/DFKI-NLP/smartdata-corpus - **Motivation:** Contains fine-grained NER labels for German. ### Checkbox - [X] Create the dataset script `/datasets/my_dataset/my_dataset.py` using the template - [X] Fill the `_DESCRIPTION` and `_CITATION` variables - [X] Implement `_infos()`, `_split_generators()` and `_generate_examples()` - [X] Make sure that the `BUILDER_CONFIGS` class attribute is filled with the different configurations of the dataset and that the `BUILDER_CONFIG_CLASS` is specified if there is a custom config class. - [X] Generate the metadata file `dataset_infos.json` for all configurations - [X] Generate the dummy data `dummy_data.zip` files to have the dataset script tested and that they don't weigh too much (<50KB) - [X] Add the dataset card `README.md` using the template : fill the tags and the various paragraphs - [X] Both tests for the real data and the dummy data pass.
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Adding OneStopEnglish corpus dataset
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This PR adds OneStopEnglish Corpus containing texts classified into reading levels (elementary, intermediate, advance) for automatic readability assessment and text simplification. Link to the paper: https://www.aclweb.org/anthology/W18-0535.pdf
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new pr for Turkish NER
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Has part
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removing unzipped hansards dummy data
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which were added by mistake
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Add CovidQA dataset
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This PR adds CovidQA, a question answering dataset specifically designed for COVID-19, built by hand from knowledge gathered from Kaggle’s COVID-19 Open Research Dataset Challenge. Link to the paper: https://arxiv.org/pdf/2004.11339.pdf Link to the homepage: https://covidqa.ai
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enriched webnlg dataset rebase
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Rebase of #1206 !
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Added kannada news headlines classification dataset.
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Manual Download of a kaggle dataset. Mostly followed process as ms_terms.
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For more information: https://www.aclweb.org/anthology/D13-1155.pdf
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Added NewsPH Raw Dataset
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Added the raw version of the NewsPH dataset, which was used to automatically generate the NewsPH-NLI corpus. Dataset of news articles in Filipino from mainstream Philippine news sites on the internet. Can be used as a language modeling dataset or to reproduce the NewsPH-NLI dataset. Paper: https://arxiv.org/abs/2010.11574 Repo: https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks
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Add KorQPair dataset
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This PR adds a [Korean paired question dataset](https://github.com/songys/Question_pair) containing labels indicating whether two questions in a given pair are semantically identical. This dataset was used to evaluate the performance of [KoGPT2](https://github.com/SKT-AI/KoGPT2#subtask-evaluations) on a phrase detection downstream task.
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arXiv dataset added
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Add Swahili news classification dataset
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adding LiMiT dataset
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Adding LiMiT: The Literal Motion in Text Dataset https://github.com/ilmgut/limit_dataset
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[doc] nlp/viewer ➡️datasets/viewer
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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cc @srush
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Added WikiText-TL-39
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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This PR adds the WikiText-TL-39 Filipino Language Modeling dataset. Paper: https://arxiv.org/abs/1907.00409 Repo: https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks
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add thainer
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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ThaiNER (v1.3) is a 6,456-sentence named entity recognition dataset created from expanding the 2,258-sentence [unnamed dataset](http://pioneer.chula.ac.th/~awirote/Data-Nutcha.zip) by [Tirasaroj and Aroonmanakun (2012)](http://pioneer.chula.ac.th/~awirote/publications/). It is used to train NER taggers in [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp). The NER tags are annotated by [Tirasaroj and Aroonmanakun (2012)]((http://pioneer.chula.ac.th/~awirote/publications/)) for 2,258 sentences and the rest by [@wannaphong](https://github.com/wannaphong/). The POS tags are done by [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp)'s `perceptron` engine trained on `orchid_ud`. [@wannaphong](https://github.com/wannaphong/) is now the only maintainer of this dataset.
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Add Naver sentiment movie corpus
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Supersedes #1168 > This PR adds the [Naver sentiment movie corpus](https://github.com/e9t/nsmc), a dataset containing Korean movie reviews from Naver, the most commonly used search engine in Korea. This dataset is often used to benchmark models on Korean NLP tasks, as seen in [this paper](https://www.aclweb.org/anthology/2020.lrec-1.199.pdf).
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Add Wiki Atomic Edits Dataset (43M edits)
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added Nergrit dataset
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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Nergrit Corpus is a dataset collection for Indonesian Named Entity Recognition, Statement Extraction, and Sentiment Analysis. This PR is only for the Named Entity Recognition.
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Add doc2dial dataset
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### Doc2dial: A Goal-Oriented Document-Grounded Dialogue Dataset v0.9 Once complete this will add the [Doc2dial](https://doc2dial.github.io/data.html) dataset from the generic data sets list.
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Update step-by-step guide about the dataset cards
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Small update in the step-by-step guide about the dataset cards to indicate it can be created and completing while exploring the dataset.
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IndoNLU benchmark is a collection of resources for training, evaluating, and analyzing natural language understanding systems for Bahasa Indonesia. It contains 12 datasets.
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Add Google Turkish Treebank Dataset
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Add Google Noun Verb Dataset
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adding bprec
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Opus elhuyar dataset for MT task having languages pair in Spanish to Basque
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Opus elhuyar dataset for MT task having languages pair in Spanish to Basque More info : http://opus.nlpl.eu/Elhuyar.php
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Multi Domain Sentiment Analysis Dataset (MDSA)
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add yelp_review_full dataset
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This corresponds to the Yelp-5 requested in https://github.com/huggingface/datasets/issues/353
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adding poem_sentiment
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Adding poem_sentiment dataset. https://github.com/google-research-datasets/poem-sentiment
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Add AmbigQA dataset
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# AmbigQA: Answering Ambiguous Open-domain Questions Dataset Adding the [AmbigQA](https://nlp.cs.washington.edu/ambigqa/) dataset as part of the sprint 🎉 (from Open dataset list for Dataset sprint) Added both the light and full versions (as seen on the dataset homepage) The json format changes based on the value of one 'type' field, so I set the unavailable field to an empty list. This is explained in the README -> Data Fields ```py train_light_dataset = load_dataset('./datasets/ambig_qa',"light",split="train") val_light_dataset = load_dataset('./datasets/ambig_qa',"light",split="validation") train_full_dataset = load_dataset('./datasets/ambig_qa',"full",split="train") val_full_dataset = load_dataset('./datasets/ambig_qa',"full",split="validation") for example in train_light_dataset: for i,t in enumerate(example['annotations']['type']): if t =='singleAnswer': # use the example['annotations']['answer'][i] # example['annotations']['qaPairs'][i] - > is [] print(example['annotations']['answer'][i]) else: # use the example['annotations']['qaPairs'][i] # example['annotations']['answer'][i] - > is [] print(example['annotations']['qaPairs'][i]) ``` - [x] All tests passed - [x] Added dummy data - [x] Added data card (as much as I could)
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Opus finlex dataset of language pair Finnish and Swedish
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Added Opus_finlex dataset of language pair Finnish and Swedish More info : http://opus.nlpl.eu/Finlex.php
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Wino bias
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The PR will fail circleCi tests because of the requirement of manual loading of data. Fresh PR because of messed up history of the previous one.
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Added ade_corpus_v2, with 3 configs for relation extraction and classification task
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Adverse Drug Reaction Data: ADE-Corpus-V2 dataset added configs for different tasks with given data
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Add Curiosity Dialogs Dataset
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Add Facebook [Curiosity Dialogs](https://github.com/facebookresearch/curiosity) Dataset.
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Add Grail QA dataset
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For more information: https://dki-lab.github.io/GrailQA/
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Add Urdu Sentiment Corpus (USC)
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@lhoestq opened a clean PR containing only relevant files. old PR #1140
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Add Urdu fake news dataset
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@lhoestq opened a clean PR containing only relevant files. old PR #1125
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Muchocine - Spanish movie reviews dataset
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add opus_100 dataset
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This PR will add [opus100 dataset](http://opus.nlpl.eu/opus-100.php).
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readme: remove link to Google's responsible AI practices
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...maybe we'll find a company that reallly stands behind responsible AI practices ;)
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Add menyo_20k_mt dataset
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Add menyo_20k_mt dataset
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Add Winobias dataset
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Pardon me for different commits with same message. There were conflicts after I rebased master while simultaneously pushing my changes to local repo, hence the duplicate entries.
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adding conceptnet5
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Adding the conceptnet5 and omcs txt files used to create the conceptnet5 dataset. Conceptne5 is a common sense dataset. More info can be found here: https://github.com/commonsense/conceptnet5/wiki
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🇸🇪 Added Swedish Reviews dataset for sentiment classification in Sw…
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perhaps: @lhoestq 🤗
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Add numeric fused head dataset
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Adding the [NFH: Numeric Fused Head](https://nlp.biu.ac.il/~lazary/fh/) dataset. Everything looks sensible and I've included both the identification and resolution tasks. I haven't personally used this dataset in my research so am unable to specify what the default configuration / supervised keys should be. I've filled out the basic info on the model card to the best of my knowledge but it's a little tricky to understand exactly what the fields represent. Dataset author: @yanaiela
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Add HKCanCor
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This PR adds the [Hong Kong Cantonese Corpus](http://compling.hss.ntu.edu.sg/hkcancor/), by [Luke and Wong 2015](http://compling.hss.ntu.edu.sg/hkcancor/data/LukeWong_Hong-Kong-Cantonese-Corpus.pdf). The dummy data included here was manually created, as the original dataset uses a xml-like format (see a copy hosted [here](https://github.com/fcbond/hkcancor/blob/master/sample/d1_v.txt) for example) that requires a few processing steps.
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add Korean HateSpeech dataset
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Add Korean NER dataset
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Supersedes #1177 > This PR adds the [Korean named entity recognition dataset](https://github.com/kmounlp/NER). This dataset has been used in many downstream tasks, such as training [KoBERT](https://github.com/SKTBrain/KoBERT) for NER, as seen in this [KoBERT-CRF implementation](https://github.com/eagle705/pytorch-bert-crf-ner).
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Add WMT20 MLQE 3 shared tasks
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3 tasks for the WMT 20 MLQE shared tasks -> 3 different datasets (I re-created #1137 because it was too messy). Note that in L199 `task3.py`, I used `logging.warning` to print some missing data in the train set.
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adding DataCommons fact checking
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Adding the data from: https://datacommons.org/factcheck/ Had to cheat a bit with the dummy data as the test doesn't recognize `.txt.gz`: had to rename uncompressed files with the `.gz` extension manually without actually compressing
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Add limit
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This PR adds [LiMiT](https://github.com/ilmgut/limit_dataset), a dataset for literal motion classification/extraction by [Manotas et al., 2020](https://www.aclweb.org/anthology/2020.findings-emnlp.88.pdf).
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Add irc disentanglement
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added files for irc disentanglement dataset was unable to test dummy data as a result of vpn/proxy issues
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adding medical-questions-pairs dataset
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This dataset consists of 3048 similar and dissimilar medical question pairs hand-generated and labeled by Curai's doctors. Dataset : https://github.com/curai/medical-question-pair-dataset Paper : https://drive.google.com/file/d/1CHPGBXkvZuZc8hpr46HeHU6U6jnVze-s/view
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add taskmaster3
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Adding Taskmaster-3 dataset https://github.com/google-research-datasets/Taskmaster/tree/master/TM-3-2020. The dataset structure almost same as original dataset with these two changes 1. In original dataset, each `apis` has a `args` filed which is a `dict` with variable keys, which represent the name and value of the args. Here converted that to a `list` of `dict` with keys `arg_name` and `arg_value`. For ex. ```python args = {"name.movie": "Mulan", "name.theater": ": "Mountain AMC 16"} ``` becomes ```python [ { "arg_name": "name.movie", "arg_value": "Mulan" }, { "arg_name": "name.theater", "arg_value": "Mountain AMC 16" } ] ``` 2. Each `apis` has a `response` which is also a `dict` with variable keys representing response name/type and it's value. As above converted it to `list` of `dict` with keys `response_name` and `response_value`.
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Add Sanskrit Classic texts in datasets
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Add large spanish corpus
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Adds a collection of Spanish corpora that can be useful for pretraining language models. Following a nice suggestion from @yjernite we provide the user with three main ways to preprocess / load either * the whole corpus (17GB!) * one specific sub-corpus * the whole corpus, but return a single split. this is useful if you want to cache the whole preprocessing step once and interact with individual sub-corpora See the dataset card for more details. Ready for review!
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Add XSUM Hallucination Annotations Dataset
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Adding Google [XSum Hallucination Annotations](https://github.com/google-research-datasets/xsum_hallucination_annotations) dataset.
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[AfriBooms] Dataset exists already
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When trying to add "AfriBooms": https://docs.google.com/spreadsheets/d/12ShVow0M6RavnzbBEabm5j5dv12zBaf0y-niwEPPlo4/edit#gid=1386399609 I noticed that the dataset exists already as a config of Universal Dependencies (universal_dependencies.py). I checked and the data exactly matches so that the new data link does not give any new data. This PR improves the config's description a bit by linking to the paper.
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Add HKCanCor
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(Apologies, didn't manage the branches properly and the PR got too messy. Going to open a new PR with everything in order)
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Adding Enriched WebNLG dataset
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This pull requests adds the `en` and `de` versions of the [Enriched WebNLG](https://github.com/ThiagoCF05/webnlg) dataset
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passed on local: ``` RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_lst20 ``` Not sure how to test: ``` RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_lst20 ``` ``` LST20 Corpus is a dataset for Thai language processing developed by National Electronics and Computer Technology Center (NECTEC), Thailand. It offers five layers of linguistic annotation: word boundaries, POS tagging, named entities, clause boundaries, and sentence boundaries. At a large scale, it consists of 3,164,002 words, 288,020 named entities, 248,181 clauses, and 74,180 sentences, while it is annotated with 16 distinct POS tags. All 3,745 documents are also annotated with one of 15 news genres. Regarding its sheer size, this dataset is considered large enough for developing joint neural models for NLP. Manually download at https://aiforthai.in.th/corpus.php ```
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Medical question pairs
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This dataset consists of 3048 similar and dissimilar medical question pairs hand-generated and labeled by Curai's doctors. Dataset : https://github.com/curai/medical-question-pair-dataset Paper : https://drive.google.com/file/d/1CHPGBXkvZuZc8hpr46HeHU6U6jnVze-s/view **No splits added**
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Windows needs special treatment again: unfortunately adding `torch` to the requirements does not work well (crashing the installation). Users should first install torch manually and then continue with the other commands. This issue arises all the time when adding torch as a dependency, but because so many novice users seem to participate in adding datasets, it may be useful to add an explicit note for Windows users to ensure that they do not run into issues.
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Turkish NER dataset, script works fine, couldn't generate dummy data
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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I've written the script (Turkish_NER.py) that includes dataset. The dataset is a zip inside another zip, and it's extracted as .DUMP file. However, after preprocessing I only get .arrow file. After I ran the script with no error messages, I get .arrow file of dataset, LICENSE and dataset_info.json.
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Add ALT
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ALT dataset -- https://www2.nict.go.jp/astrec-att/member/mutiyama/ALT/
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add taskmaster-2
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Adding taskmaster-2 dataset. https://github.com/google-research-datasets/Taskmaster/tree/master/TM-2-2020
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Add IWSLT'15 English-Vietnamese machine translation Data
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Preprocessed Dataset from IWSLT'15 English-Vietnamese machine translation: English-Vietnamese. from https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/
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addition of py_ast
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The dataset consists of parsed Parsed ASTs that were used to train and evaluate the DeepSyn tool. The Python programs are collected from GitHub repositories by removing duplicate files, removing project forks (copy of another existing repository) ,keeping only programs that parse and have at most 30'000 nodes in the AST and we aim to remove obfuscated files
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Add msr_text_compression
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Add [MSR Abstractive Text Compression Dataset](https://msropendata.com/datasets/f8ce2ec9-7fbd-48f7-a8bb-2d2279373563)
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add taskmaster-1
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Adding Taskmaster-1 dataset https://github.com/google-research-datasets/Taskmaster/tree/master/TM-1-2019
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Add NewsPH_NLI dataset
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This PR adds the NewsPH-NLI Dataset, the first benchmark dataset for sentence entailment in the low-resource Filipino language. Constructed through exploting the structure of news articles. Contains 600,000 premise-hypothesis pairs, in 70-15-15 split for training, validation, and testing. Link to the paper: https://arxiv.org/pdf/2010.11574.pdf Link to the dataset/repo: https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks
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Added Translator Human Parity Data For a Chinese-English news transla…
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…tion system from Open dataset list for Dataset sprint, Microsoft Datasets tab.
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Add Fake News Detection in Filipino dataset
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This PR adds the Fake News Filipino Dataset, a low-resource fake news detection corpora in Filipino. Contains 3,206 expertly-labeled news samples, half of which are real and half of which are fake. Link to the paper: http://www.lrec-conf.org/proceedings/lrec2020/index.html Link to the dataset/repo: https://github.com/jcblaisecruz02/Tagalog-fake-news
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Add Dengue dataset in Filipino
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This PR adds the Dengue Dataset, a benchmark dataset for low-resource multiclass classification, with 4,015 training, 500 testing, and 500 validation examples, each labeled as part of five classes. Each sample can be a part of multiple classes. Collected as tweets. Link to the paper: https://ieeexplore.ieee.org/document/8459963 Link to the dataset/repo: https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks
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adding hind_encorp dataset
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adding Hindi_Encorp05 dataset
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Added AQUA-RAT (Algebra Question Answering with Rationales) Dataset
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all test passed
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need help creating dummy data
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Add Hate Speech Dataset in Filipino
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This PR adds the Hate Speech Dataset, a text classification dataset in Filipino, consisting 10k tweets (training set) that are labeled as hate speech or non-hate speech. Released with 4,232 validation and 4,232 testing samples. Collected during the 2016 Philippine Presidential Elections. Link to the paper: https://pcj.csp.org.ph/index.php/pcj/issue/download/29/PCJ%20V14%20N1%20pp1-14%202019 Link to the dataset/repo: https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks
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Add Adversarial SQuAD dataset
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# Adversarial SQuAD Adding the Adversarial [SQuAD](https://github.com/robinjia/adversarial-squad) dataset as part of the sprint 🎉 This dataset adds adversarial sentences to a subset of the SQuAD dataset's dev examples. How to get the original squad example id is explained in readme->Data Instances. The whole data is intended for use in evaluation. (Which could of course be also used for training if one wants). So there is no classical train/val/test split, but a split based on the number of adversaries added. There are 2 splits of this dataset: - AddSent: Has up to five candidate adversarial sentences that don't answer the question, but have a lot of words in common with the question. This adversary is does not query the model in any way. - AddOneSent: Similar to AddSent, but just one candidate sentences was picked at random. This adversary is does not query the model in any way. (The AddAny and AddCommon datasets mentioned in the paper are dynamically generated based on model's output distribution thus are not included here) The failing test look like some unrelated timeout thing, will probably clear if rerun. - [x] All tests passed - [x] Added dummy data - [x] Added data card (as much as I could)
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add mkb dataset
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This PR will add Mann Ki Baat dataset (parallel data for Indian languages).
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ADD COVID-QA dataset
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This PR adds the COVID-QA dataset, a question answering dataset consisting of 2,019 question/answer pairs annotated by volunteer biomedical experts on scientific articles related to COVID-19 Link to the paper: https://openreview.net/forum?id=JENSKEEzsoU Link to the dataset/repo: https://github.com/deepset-ai/COVID-QA
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added emotions detection in arabic dataset
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Dataset for Emotions detection in Arabic text more info: https://github.com/AmrMehasseb/Emotional-Tone
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Add KorQuAD v2 Dataset
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# The Korean Question Answering Dataset v2 Adding the [KorQuAD](https://korquad.github.io/) v2 dataset as part of the sprint 🎉 This dataset is very similar to SQuAD and is an extension of [squad_kor_v1](https://github.com/huggingface/datasets/pull/1178) which is why I added it as `squad_kor_v2`. - Crowd generated questions and answer (1-answer per question) for Wikipedia articles. Differently from V1 it includes the html structure and markup, which makes it a different enough dataset. (doesn't share ids between v1 and v2 either) - [x] All tests passed - [x] Added dummy data - [x] Added data card (as much as I could) Edit: 🤦 looks like squad_kor_v1 commit sneaked in here too
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Small update to the doc: add flatten_indices in doc
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Add KorQuAD v1 Dataset
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# The Korean Question Answering Dataset Adding the [KorQuAD](https://korquad.github.io/KorQuad%201.0/) v1 dataset as part of the sprint 🎉 This dataset is very similar to SQuAD which is why I added it as `squad_kor_v1`. There is also a v2 which I added [here](https://github.com/huggingface/datasets/pull/1180). - Crowd generated questions and answer (1-answer per question) for Wikipedia articles. - [x] All tests passed - [x] Added dummy data - [x] Added data card (as much as I could)
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Add Korean NER dataset
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This PR adds the [Korean named entity recognition dataset](https://github.com/kmounlp/NER). This dataset has been used in many downstream tasks, such as training [KoBERT](https://github.com/SKTBrain/KoBERT) for NER, as seen in this [KoBERT-CRF implementation](https://github.com/eagle705/pytorch-bert-crf-ner).
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Add OpenPI Dataset
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Add the OpenPI Dataset by AI2 (AllenAI)
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added ReDial dataset
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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Updating README Dataset link: https://redialdata.github.io/website/datasheet
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Add Universal Morphologies
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[ "Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)." ]
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Adding unimorph universal morphology annotations for 110 languages, pfew!!! one lemma per row with all possible forms and annotations https://unimorph.github.io/
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add wikipedia biography dataset
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My first PR containing the Wikipedia biographies dataset. I have followed all the steps in the [guide](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md). It passes all the tests.
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Add proto_qa dataset
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Added dataset tags as required.
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