Datasets:
The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: FileNotFoundError
Message: http://oma-project.com/ArSenL/ArSenTD-LEV.zip
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/http.py", line 414, in _info
await _file_info(
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/http.py", line 849, in _file_info
r.raise_for_status()
File "/src/services/worker/.venv/lib/python3.9/site-packages/aiohttp/client_reqrep.py", line 1060, in raise_for_status
raise ClientResponseError(
aiohttp.client_exceptions.ClientResponseError: 404, message='Not Found', url=URL('http://oma-project.com/ArSenL/ArSenTD-LEV.zip')
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 126, in get_rows_or_raise
return get_rows(
File "/src/services/worker/src/worker/utils.py", line 64, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 103, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1388, in __iter__
for key, example in ex_iterable:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 234, in __iter__
yield from self.generate_examples_fn(**self.kwargs)
File "/tmp/modules-cache/datasets_modules/datasets/arsentd_lev/baefb80123b3164550ac5d941ce9c1a3f41e92f1b525a71f8f29e0869f172d7a/arsentd_lev.py", line 79, in _generate_examples
with open(path, encoding="utf-8") as f:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/streaming.py", line 75, in wrapper
return function(*args, download_config=download_config, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 512, in xopen
file_obj = fsspec.open(file, mode=mode, *args, **kwargs).open()
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 452, in open
out = open_files(
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 280, in open_files
fs, fs_token, paths = get_fs_token_paths(
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 622, in get_fs_token_paths
fs = filesystem(protocol, **inkwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/registry.py", line 290, in filesystem
return cls(**storage_options)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 79, in __call__
obj = super().__call__(*args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/zip.py", line 56, in __init__
self.fo = fo.__enter__() # the whole instance is a context
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 100, in __enter__
f = self.fs.open(self.path, mode=mode)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 1307, in open
f = self._open(
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/http.py", line 353, in _open
size = size or self.info(path, **kwargs)["size"]
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/asyn.py", line 118, in wrapper
return sync(self.loop, func, *args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/asyn.py", line 103, in sync
raise return_result
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/asyn.py", line 56, in _runner
result[0] = await coro
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/http.py", line 427, in _info
raise FileNotFoundError(url) from exc
FileNotFoundError: http://oma-project.com/ArSenL/ArSenTD-LEV.zipNeed help to make the dataset viewer work? Open a discussion for direct support.
Dataset Card for ArSenTD-LEV
Dataset Summary
The Arabic Sentiment Twitter Dataset for Levantine dialect (ArSenTD-LEV) contains 4,000 tweets written in Arabic and equally retrieved from Jordan, Lebanon, Palestine and Syria.
Supported Tasks and Leaderboards
Sentriment analysis
Languages
Arabic Levantine Dualect
Dataset Structure
Data Instances
{'Country': 0, 'Sentiment': 3, 'Sentiment_Expression': 0, 'Sentiment_Target': 'هاي سوالف عصابات ارهابية', 'Topic': 'politics', 'Tweet': 'ثلاث تفجيرات في #كركوك الحصيلة قتيل و 16 جريح بدأت اكلاوات كركوك كانت امان قبل دخول القوات العراقية ، هاي سوالف عصابات ارهابية'}
Data Fields
Tweet: the text content of the tweet Country: the country from which the tweet was collected ('jordan', 'lebanon', 'syria', 'palestine')Topic: the topic being discussed in the tweet (personal, politics, religion, sports, entertainment and others) Sentiment: the overall sentiment expressed in the tweet (very_negative, negative, neutral, positive and very_positive) Sentiment_Expression: the way how the sentiment was expressed: explicit, implicit, or none (the latter when sentiment is neutral) Sentiment_Target: the segment from the tweet to which sentiment is expressed. If sentiment is neutral, this field takes the 'none' value.
Data Splits
No standard splits are provided
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
Make sure to read and agree to the license
Citation Information
@article{baly2019arsentd,
title={Arsentd-lev: A multi-topic corpus for target-based sentiment analysis in arabic levantine tweets},
author={Baly, Ramy and Khaddaj, Alaa and Hajj, Hazem and El-Hajj, Wassim and Shaban, Khaled Bashir},
journal={arXiv preprint arXiv:1906.01830},
year={2019}
}
Contributions
Thanks to @moussaKam for adding this dataset.
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