Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+- crowdsourced
+language_creators:
+- found
+languages:
+- apc
+- apj
+licenses:
+- other-Copyright-2018-by-[American-University-of-Beirut]
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K"
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- sentiment-classification
+- topic-classification
+---
+
+# Dataset Card for ArSenTD-LEV
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** [ArSenTD-LEV homepage](http://oma-project.com/)
+- **Paper:** [ArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine Tweets](https://arxiv.org/abs/1906.01830)
+
+### 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](http://oma-project.com/ArSenL/ArSenTD_Lev_Intro)
+
+### 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}
+}
+```

arsentd_lev.py

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+# coding=utf-8
+# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Lint as: python3
+"""ArSenTD-Lev :  Arabic Sentiment Twitter Dataset for LEVantine dialect"""
+
+from __future__ import absolute_import, division, print_function
+
+import os
+
+import datasets
+
+
+_CITATION = """
+@article{ArSenTDLev2018,
+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 Bashir Shaban, Khaled},
+journal={OSACT3},
+pages={},
+year={2018}}
+"""
+
+_DESCRIPTION = """
+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.
+"""
+
+_URL = "http://oma-project.com/ArSenL/ArSenTD-LEV.zip"
+_FEATURES = ["Tweet", "Country", "Topic", "Sentiment", "Sentiment_Expression", "Sentiment_Target"]
+
+
+class ArsentdLev(datasets.GeneratorBasedBuilder):
+    """"ArSenTD-Lev Dataset"""
+
+    VERSION = datasets.Version("1.1.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "Tweet": datasets.Value("string"),
+                    "Country": datasets.ClassLabel(names=["jordan", "lebanon", "syria", "palestine"]),
+                    "Topic": datasets.Value("string"),
+                    "Sentiment": datasets.ClassLabel(
+                        names=["negative", "neutral", "positive", "very_negative", "very_positive"]
+                    ),
+                    "Sentiment_Expression": datasets.ClassLabel(names=["explicit", "implicit", "none"]),
+                    "Sentiment_Target": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            homepage="http://oma-project.com/ArSenL/ArSenTD_Lev_Intro",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        path = dl_manager.download_and_extract(_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"path": os.path.join(path, "ArSenTD-LEV.tsv")},
+            ),
+        ]
+
+    def _generate_examples(self, path=None):
+        """Yields examples."""
+        with open(path, encoding="utf-8") as f:
+            f.readline()  # skip first line
+            for idx, line in enumerate(f):
+                yield idx, {el[0]: el[1].strip() for el in zip(_FEATURES, line.split("\t"))}

dataset_infos.json

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+{"default": {"description": "\nThe 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.\n", "citation": "\n@article{ArSenTDLev2018,\ntitle={ArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine Tweets},\nauthor={Baly, Ramy, and Khaddaj, Alaa and Hajj, Hazem and El-Hajj, Wassim and Bashir Shaban, Khaled},\njournal={OSACT3},\npages={},\nyear={2018}}\n", "homepage": "http://oma-project.com/ArSenL/ArSenTD_Lev_Intro", "license": "", "features": {"Tweet": {"dtype": "string", "id": null, "_type": "Value"}, "Country": {"num_classes": 4, "names": ["jordan", "lebanon", "syria", "palestine"], "names_file": null, "id": null, "_type": "ClassLabel"}, "Topic": {"dtype": "string", "id": null, "_type": "Value"}, "Sentiment": {"num_classes": 5, "names": ["negative", "neutral", "positive", "very_negative", "very_positive"], "names_file": null, "id": null, "_type": "ClassLabel"}, "Sentiment_Expression": {"num_classes": 3, "names": ["explicit", "implicit", "none"], "names_file": null, "id": null, "_type": "ClassLabel"}, "Sentiment_Target": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "arsentd_lev", "config_name": "default", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1233980, "num_examples": 4000, "dataset_name": "arsentd_lev"}}, "download_checksums": {"http://oma-project.com/ArSenL/ArSenTD-LEV.zip": {"num_bytes": 392666, "checksum": "399d03bf6e8eb50415355132bc6742b2d7a9728070f6f789d705616fd12189c3"}}, "download_size": 392666, "post_processing_size": null, "dataset_size": 1233980, "size_in_bytes": 1626646}}

dummy/1.1.0/dummy_data.zip

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+size 1451