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adding opus_openoffice
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Adding Opus OpenOffice: http://opus.nlpl.eu/OpenOffice.php
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Add Danish NER dataset
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arxiv dataset added
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**adding arXiv dataset**: arXiv dataset and metadata of 1.7M+ scholarly papers across STEM
dataset link: https://www.kaggle.com/Cornell-University/arxiv
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WIP
As some tests did not clear! 👎🏼
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can't load "german_legal_entity_recognition" dataset
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2020-12-08T12:42:01Z
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2020-12-16T16:03:13Z
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NONE
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Add OPUS Ted Talks 2013
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The Snips Built In Intents 2016 dataset.
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2020-12-08T15:27:52Z
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2020-12-08T15:27:52Z
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This PR proposes to add the Snips.ai built in intents dataset. The first configuration added is for the intent labels only, but the dataset includes entity slots that may in future be added as alternate configurations.
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2020-12-11T17:42:20Z
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2020-12-08T11:24:16Z
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2020-12-08T18:44:20Z
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2020-12-08T18:41:23Z
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Adding EUconst, a parallel corpus collected from the European Constitution.
21 languages, 210 bitexts
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2020-12-08T11:16:41Z
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2020-12-08T11:34:47Z
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2020-12-08T11:34:38Z
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2020-12-08T11:05:44Z
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2020-12-09T08:54:50Z
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Pubmed QA dataset:
PQA-L(abeled) 1k
PQA-U(labeled) 61.2k
PQA-A(rtifical labeled) 211.3k
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2020-12-08T10:47:36Z
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2020-12-24T17:38:09Z
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2020-12-24T17:38:09Z
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CONTRIBUTOR
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hi
please find error below getting imdb train spli:
thanks
`
datasets.load_dataset>>> datasets.load_dataset("imdb", split="train")`
errors
```
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
Downloading and preparing dataset imdb/plain_text (download: 80.23 MiB, generated: 127.06 MiB, post-processed: Unknown size, total: 207.28 MiB) to /idiap/temp/rkarimi/cache_home_1/datasets/imdb/plain_text/1.0.0/90099cb476936b753383ba2ae6ab2eae419b2e87f71cd5189cb9c8e5814d12a3...
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets/downloads
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py", line 558, in _download_and_prepare
verify_splits(self.info.splits, split_dict)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/info_utils.py", line 73, in verify_splits
raise NonMatchingSplitsSizesError(str(bad_splits))
datasets.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='unsupervised', num_bytes=67125548, num_examples=50000, dataset_name='imdb'), 'recorded': SplitInfo(name='unsupervised', num_bytes=7486451, num_examples=5628, dataset_name='imdb')}]
```
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The dataset requires manually downloading data from Kaggle.
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| 759,309,457 |
MDExOlB1bGxSZXF1ZXN0NTM0MzM2Mzgz
| 1,288 |
Add CodeSearchNet corpus dataset
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2020-12-08T10:07:50Z
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2020-12-09T17:05:28Z
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2020-12-09T17:05:28Z
|
CONTRIBUTOR
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This PR adds the CodeSearchNet corpus proxy dataset for semantic code search: https://github.com/github/CodeSearchNet
I have had a few issues, mentioned below. Would appreciate some help on how to solve them.
## Issues generating dataset card
Is there something wrong with my declaration of the dataset features ?
```
features=datasets.Features(
{
"repository_name": datasets.Value("string"),
"func_path_in_repository": datasets.Value("string"),
"func_name": datasets.Value("string"),
"whole_func_string": datasets.Value("string"),
"language": datasets.Value("string"),
"func_code_string": datasets.Value("string"),
"func_code_tokens": datasets.Sequence(datasets.Value("string")),
"func_documentation_string": datasets.Value("string"),
"func_documentation_tokens": datasets.Sequence(datasets.Value("string")),
"split_name": datasets.Value("string"),
"func_code_url": datasets.Value("string"),
# TODO - add licensing info in the examples
}
),
```
When running the streamlite app for tagging the dataset on my machine, I get the following error :
## Issues with dummy data
Due to the unusual structure of the data, I have been unable to generate dummy data automatically.
I tried to generate it manually, but pytests fail when using the manually-generated dummy data ! Pytests work fine when using the real data.
```
============================================================================================== test session starts ==============================================================================================
platform linux -- Python 3.7.9, pytest-6.1.2, py-1.9.0, pluggy-0.13.1
plugins: xdist-2.1.0, forked-1.3.0
collected 1 item
tests/test_dataset_common.py F [100%]
=================================================================================================== FAILURES ====================================================================================================
________________________________________________________________________ LocalDatasetTest.test_load_dataset_all_configs_code_search_net _________________________________________________________________________
self = <tests.test_dataset_common.LocalDatasetTest testMethod=test_load_dataset_all_configs_code_search_net>, dataset_name = 'code_search_net'
@slow
def test_load_dataset_all_configs(self, dataset_name):
configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)
> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True)
tests/test_dataset_common.py:237:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tests/test_dataset_common.py:198: in check_load_dataset
self.parent.assertTrue(len(dataset[split]) > 0)
E AssertionError: False is not true
--------------------------------------------------------------------------------------------- Captured stdout call ----------------------------------------------------------------------------------------------
Downloading and preparing dataset code_search_net/all (download: 1.00 MiB, generated: 1.00 MiB, post-processed: Unknown size, total: 2.00 MiB) to /tmp/tmppx78sj24/code_search_net/all/1.0.0...
Dataset code_search_net downloaded and prepared to /tmp/tmppx78sj24/code_search_net/all/1.0.0. Subsequent calls will reuse this data.
--------------------------------------------------------------------------------------------- Captured stderr call ----------------------------------------------------------------------------------------------
... (irrelevant info - Deprecation warnings)
============================================================================================ short test summary info ============================================================================================
FAILED tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_code_search_net - AssertionError: False is not true
========================================================================================= 1 failed, 4 warnings in 3.00s ========================================================================================
```
## Note : Data structure in S3
The data is stored on S3, and organized by programming languages.
It is stored in the following repository structure:
```
.
├── <language_name> # e.g. python
│ └── final
│ └── jsonl
│ ├── test
│ │ └── <language_name>_test_0.jsonl.gz
│ ├── train
│ │ ├── <language_name>_train_0.jsonl.gz
│ │ ├── <language_name>_train_1.jsonl.gz
│ │ ├── ...
│ │ └── <language_name>_train_n.jsonl.gz
│ └── valid
│ └── <language_name>_valid_0.jsonl.gz
├── <language_name>_dedupe_definitions_v2.pkl
└── <language_name>_licenses.pkl
```
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MDU6SXNzdWU3NTkzMDA5OTI=
| 1,287 |
'iwslt2017-ro-nl', cannot be downloaded
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2020-12-08T09:56:55Z
|
2022-06-13T10:41:33Z
|
2022-06-13T10:41:33Z
|
CONTRIBUTOR
| null | null | null |
Hi
I am trying
`>>> datasets.load_dataset("iwslt2017", 'iwslt2017-ro-nl', split="train")`
getting this error thank you for your help
```
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
Downloading and preparing dataset iwsl_t217/iwslt2017-ro-nl (download: 314.07 MiB, generated: 39.92 MiB, post-processed: Unknown size, total: 354.00 MiB) to /idiap/temp/rkarimi/cache_home_1/datasets/iwsl_t217/iwslt2017-ro-nl/1.0.0/cca6935a0851a8ceac1202a62c958738bdfa23c57a51bc52ac1c5ebd2aa172cd...
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets/downloads
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File " /idiap/home/rkarimi/.cache/huggingface/modules/datasets_modules/datasets/iwslt2017/cca6935a0851a8ceac1202a62c958738bdfa23c57a51bc52ac1c5ebd2aa172cd/iwslt2017.py", line 118, in _split_generators
dl_dir = dl_manager.download_and_extract(MULTI_URL)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 216, in map_nested
return function(data_struct)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 477, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://wit3.fbk.eu/archive/2017-01-trnmted//texts/DeEnItNlRo/DeEnItNlRo/DeEnItNlRo-DeEnItNlRo.tgz
```
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[libprotobuf FATAL /sentencepiece/src/../third_party/protobuf-lite/google/protobuf/repeated_field.h:1505] CHECK failed: (index) >= (0): terminate called after throwing an instance of 'google::protobuf::FatalException' what(): CHECK failed: (index) >= (0): Aborted
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2020-12-08T09:44:15Z
|
2020-12-12T19:36:22Z
|
2020-12-12T16:22:36Z
|
CONTRIBUTOR
| null | null | null |
Hi
I am getting this error when evaluating on wmt16-ro-en using finetune_trainer.py of huggingface repo. thank for your help
{'epoch': 20.0}
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 20/20 [00:16<00:00, 1.22it/s]
12/08/2020 10:41:19 - INFO - seq2seq.trainers.trainer - Saving model checkpoint to outputs/experiment/joint/finetune/lr-2e-5
12/08/2020 10:41:24 - INFO - __main__ - {'wmt16-en-ro': Dataset(features: {'src_texts': Value(dtype='string', id=None), 'task': Value(dtype='string', id=None), 'tgt_texts': Value(dtype='string', id=None)}, num_rows: 1998), 'qnli': Dataset(features: {'src_texts': Value(dtype='string', id=None), 'task': Value(dtype='string', id=None), 'tgt_texts': Value(dtype='string', id=None)}, num_rows: 5462), 'scitail': Dataset(features: {'src_texts': Value(dtype='string', id=None), 'task': Value(dtype='string', id=None), 'tgt_texts': Value(dtype='string', id=None)}, num_rows: 1303)}
12/08/2020 10:41:24 - INFO - __main__ - *** Evaluate ***
12/08/2020 10:41:24 - INFO - seq2seq.utils.utils - using task specific params for wmt16-en-ro: {'max_length': 300, 'num_beams': 4}
12/08/2020 10:41:24 - INFO - seq2seq.trainers.trainer - ***** Running Evaluation *****
12/08/2020 10:41:24 - INFO - seq2seq.trainers.trainer - Num examples = 1998
12/08/2020 10:41:24 - INFO - seq2seq.trainers.trainer - Batch size = 64
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 32/32 [00:37<00:00, 1.19s/it][libprotobuf FATAL /sentencepiece/src/../third_party/protobuf-lite/google/protobuf/repeated_field.h:1505] CHECK failed: (index) >= (0):
terminate called after throwing an instance of 'google::protobuf::FatalException'
what(): CHECK failed: (index) >= (0):
Aborted
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| 759,278,758 |
MDU6SXNzdWU3NTkyNzg3NTg=
| 1,285 |
boolq does not work
|
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2020-12-08T09:28:47Z
|
2020-12-08T09:47:10Z
|
2020-12-08T09:47:10Z
|
CONTRIBUTOR
| null | null | null |
Hi
I am getting this error when trying to load boolq, thanks for your help
ts_boolq_default_0.1.0_2987db1f15deaa19500ae24de560eabeaf1f8ef51df88c0470beeec72943bf11.lock
Traceback (most recent call last):
File "finetune_t5_trainer.py", line 274, in <module>
main()
File "finetune_t5_trainer.py", line 147, in main
for task in data_args.tasks]
File "finetune_t5_trainer.py", line 147, in <listcomp>
for task in data_args.tasks]
File "/remote/idiap.svm/user.active/rkarimi/dev/ruse/seq2seq/tasks/tasks.py", line 58, in get_dataset
dataset = self.load_dataset(split=split)
File "/remote/idiap.svm/user.active/rkarimi/dev/ruse/seq2seq/tasks/tasks.py", line 54, in load_dataset
return datasets.load_dataset(self.task.name, split=split)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File " /idiap/home/rkarimi/.cache/huggingface/modules/datasets_modules/datasets/boolq/2987db1f15deaa19500ae24de560eabeaf1f8ef51df88c0470beeec72943bf11/boolq.py", line 74, in _split_generators
downloaded_files = dl_manager.download_custom(urls_to_download, tf.io.gfile.copy)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 149, in download_custom
custom_download(url, path)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/tensorflow/python/lib/io/file_io.py", line 516, in copy_v2
compat.path_to_bytes(src), compat.path_to_bytes(dst), overwrite)
tensorflow.python.framework.errors_impl.AlreadyExistsError: file already exists
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MDExOlB1bGxSZXF1ZXN0NTM0MzAzNDk0
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Update coqa dataset url
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2020-12-08T09:16:38Z
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2020-12-08T18:19:09Z
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2020-12-08T18:19:09Z
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`datasets.stanford.edu` is invalid.
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MDExOlB1bGxSZXF1ZXN0NTM0Mjg4MDg2
| 1,283 |
Add dutch book review dataset
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2020-12-08T08:50:48Z
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2020-12-09T20:21:58Z
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2020-12-09T17:25:25Z
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- Name: Dutch Book Review Dataset (DBRD)
- Description: The DBRD (pronounced dee-bird) dataset contains over 110k book reviews along with associated binary sentiment polarity labels and is intended as a benchmark for sentiment classification in Dutch.
- Paper: https://arxiv.org/abs/1910.00896
- Data: https://github.com/benjaminvdb/DBRD
- Motivation: A large (real-life) dataset of Dutch book reviews and sentiment polarity (positive/negative), based on the associated rating.
Checks
- [x] Create the dataset script /datasets/dbrd/dbrd.py using the template
- [x] Fill the _DESCRIPTION and _CITATION variables
- [x] Implement _info(), _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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MDExOlB1bGxSZXF1ZXN0NTM0MjQ4NzI5
| 1,282 |
add thaiqa_squad
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2020-12-08T18:36:18Z
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2020-12-08T18:36:18Z
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Example format is a little different from SQuAD since `thaiqa` always have one answer per question so I added a check to convert answers to lists if they are not already one to future-proof additional questions that might have multiple answers.
`thaiqa_squad` is an open-domain, extractive question answering dataset (4,000 questions in `train` and 74 questions in `dev`) in [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format, originally created by [NECTEC](https://www.nectec.or.th/en/) from Wikipedia articles and adapted to [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format by [PyThaiNLP](https://github.com/PyThaiNLP/).
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adding hybrid_qa
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MEMBER
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Adding HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data
https://github.com/wenhuchen/HybridQA
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disaster response messages dataset
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2020-12-08T07:27:16Z
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2020-12-09T16:21:57Z
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2020-12-09T16:21:57Z
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added para_pat
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2020-12-08T06:28:47Z
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2020-12-14T13:41:17Z
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2020-12-14T13:41:17Z
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Dataset link : https://figshare.com/articles/ParaPat_The_Multi-Million_Sentences_Parallel_Corpus_of_Patents_Abstracts/12627632
Working on README.md currently
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Craigslist bargains
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2020-12-08T01:45:55Z
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2020-12-09T00:46:15Z
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2020-12-09T00:46:15Z
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`craigslist_bargains` dataset from [here](https://worksheets.codalab.org/worksheets/0x453913e76b65495d8b9730d41c7e0a0c/)
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add One Million Posts Corpus
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2020-12-11T18:28:18Z
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2020-12-11T18:28:18Z
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- **Name:** One Million Posts Corpus
- **Description:** The “One Million Posts” corpus is an annotated data set consisting of user comments posted to an Austrian newspaper website (in German language).
- **Paper:** https://dl.acm.org/doi/10.1145/3077136.3080711
- **Data:** https://github.com/OFAI/million-post-corpus
- **Motivation:** Big German (real-life) dataset containing different annotations around forum moderation with expert annotations.
### 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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Yoruba GV NER added
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2020-12-08T00:31:38Z
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2020-12-08T23:25:28Z
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2020-12-08T23:25:28Z
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I just added Yoruba GV NER dataset from this paper https://www.aclweb.org/anthology/2020.lrec-1.335/
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MDExOlB1bGxSZXF1ZXN0NTM0MDI0MTQx
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oclar-dataset
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2020-12-07T23:56:45Z
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2020-12-09T15:36:08Z
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2020-12-09T15:36:08Z
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Opinion Corpus for Lebanese Arabic Reviews (OCLAR) corpus is utilizable for Arabic sentiment classification on reviews, including hotels, restaurants, shops, and others. : [homepage](http://archive.ics.uci.edu/ml/datasets/Opinion+Corpus+for+Lebanese+Arabic+Reviews+%28OCLAR%29#)
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Created wiki_movies dataset.
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2020-12-07T23:38:54Z
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2020-12-14T13:56:49Z
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2020-12-14T13:56:49Z
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First PR (ever). Hopefully this movies dataset is useful to others!
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2020-12-07T23:19:36Z
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2020-12-07T23:48:05Z
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SMS Spam Dataset
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2020-12-08T17:42:19Z
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2020-12-08T17:42:19Z
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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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2020-12-07T23:03:48Z
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2020-12-08T17:41:23Z
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2020-12-08T17:41:23Z
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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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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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which were added by mistake
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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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Rebase of #1206 !
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MDExOlB1bGxSZXF1ZXN0NTMzNzY4OTgy
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Add Google Sentence Compression dataset
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For more information: https://www.aclweb.org/anthology/D13-1155.pdf
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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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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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Add Swahili news classification dataset
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Adding LiMiT: The Literal Motion in Text Dataset
https://github.com/ilmgut/limit_dataset
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cc @srush
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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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2020-12-08T14:44:49Z
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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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2020-12-07T13:33:45Z
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2020-12-08T14:32:33Z
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2020-12-08T14:21:37Z
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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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2020-12-14T10:05:01Z
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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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2020-12-07T12:39:09Z
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2020-12-14T16:17:14Z
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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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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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2020-12-07T11:38:45Z
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2020-12-08T14:11:50Z
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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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Opus elhuyar dataset for MT task having languages pair in Spanish to Basque
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Adding poem_sentiment dataset.
https://github.com/google-research-datasets/poem-sentiment
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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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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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Adverse Drug Reaction Data: ADE-Corpus-V2 dataset added configs for different tasks with given data
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Add Facebook [Curiosity Dialogs](https://github.com/facebookresearch/curiosity) Dataset.
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For more information: https://dki-lab.github.io/GrailQA/
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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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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 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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perhaps: @lhoestq 🤗
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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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2020-12-09T16:34:18Z
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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 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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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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2020-12-16T16:18:25Z
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2020-12-16T16:18:25Z
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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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2020-12-09T14:42:53Z
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2020-12-09T14:42:53Z
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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
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```
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```
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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2020-12-07T19:04:08Z
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Add large spanish corpus
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2020-12-09T13:36:36Z
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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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2020-12-06T16:40:19Z
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2020-12-20T13:34:56Z
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2020-12-16T16:57:11Z
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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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2020-12-06T16:35:13Z
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2020-12-07T16:52:24Z
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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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2020-12-06T20:23:17Z
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2020-12-06T20:21:54Z
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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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Add msr_genomics_kbcomp Dataset
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Adding Enriched WebNLG dataset
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2020-12-09T09:40:32Z
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2020-12-09T09:40:32Z
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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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add lst20 with manual download
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2020-12-06T14:49:10Z
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2020-12-09T16:33:10Z
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2020-12-09T16:33:10Z
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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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adding meta_woz dataset
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2020-12-16T15:05:25Z
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