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README.md

@@ -1,226 +0,0 @@
----
-annotations_creators:
-- expert-generated
-language_creators:
-- found
-languages:
-- ar
-- da
-- en
-- gr
-- tr
-licenses:
-- cc-by-4.0
-multilinguality:
-- multilingual
-pretty_name: OffensEval 2020
-size_categories:
-- 10K<n<100K
-source_datasets:
-- original
-task_categories:
-- text-classification
-task_ids:
-- hate-speech-detection
-- text-classification-other-hate-speech-detection
-extra_gated_prompt: "Warning: this repository contains harmful content (abusive language, hate speech)."
-paperswithcode_id: 
-- dkhate
-- ogtd
----
-
-# Dataset Card for "offenseval_2020"
-
-## Table of Contents
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits)
-- [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)
-  - [Contributions](#contributions)
-
-## Dataset Description
-
-- **Homepage:** [https://sites.google.com/site/offensevalsharedtask/results-and-paper-submission](https://sites.google.com/site/offensevalsharedtask/results-and-paper-submission)
-- **Repository:** 
-- **Paper:** [https://aclanthology.org/2020.semeval-1.188/](https://aclanthology.org/2020.semeval-1.188/), [https://arxiv.org/abs/2006.07235](https://arxiv.org/abs/2006.07235)
-- **Point of Contact:** [Leon Derczynski](https://github.com/leondz)
-
-### Dataset Summary
-
-OffensEval 2020 features a multilingual dataset with five languages. The languages included in OffensEval 2020 are:
-
-* Arabic
-* Danish
-* English
-* Greek
-* Turkish
-
-The annotation follows the hierarchical tagset proposed in the Offensive Language Identification Dataset (OLID) and used in OffensEval 2019. 
-In this taxonomy we break down offensive content into the following three sub-tasks taking the type and target of offensive content into account. 
-The following sub-tasks were organized:
-
-* Sub-task A - Offensive language identification;
-* Sub-task B - Automatic categorization of offense types;
-* Sub-task C - Offense target identification.
-
-English training data is omitted so needs to be collected otherwise (see [https://zenodo.org/record/3950379#.XxZ-aFVKipp](https://zenodo.org/record/3950379#.XxZ-aFVKipp))
-
-The source datasets come from:
-
-* Arabic [https://arxiv.org/pdf/2004.02192.pdf](https://arxiv.org/pdf/2004.02192.pdf), [https://aclanthology.org/2021.wanlp-1.13/](https://aclanthology.org/2021.wanlp-1.13/)
-* Danish [https://arxiv.org/pdf/1908.04531.pdf](https://arxiv.org/pdf/1908.04531.pdf), [https://aclanthology.org/2020.lrec-1.430/?ref=https://githubhelp.com](https://aclanthology.org/2020.lrec-1.430/)
-* English [https://arxiv.org/pdf/2004.14454.pdf](https://arxiv.org/pdf/2004.14454.pdf), [https://aclanthology.org/2021.findings-acl.80.pdf](https://aclanthology.org/2021.findings-acl.80.pdf)
-* Greek [https://arxiv.org/pdf/2003.07459.pdf](https://arxiv.org/pdf/2003.07459.pdf), [https://aclanthology.org/2020.lrec-1.629/](https://aclanthology.org/2020.lrec-1.629/)
-* Turkish [https://aclanthology.org/2020.lrec-1.758/](https://aclanthology.org/2020.lrec-1.758/)
-
-### Supported Tasks and Leaderboards
-
-* [OffensEval 2020](https://sites.google.com/site/offensevalsharedtask/results-and-paper-submission)
-
-### Languages
-
-Five are covered: bcp47 `ar;da;en;gr;tr`
-
-## Dataset Structure
-
-There are five named configs, one per language:
-
-* `ar` Arabic
-* `da` Danish
-* `en` English
-* `gr` Greek
-* `tr` Turkish
-
-The training data for English is absent - this is 9M tweets that need to be rehydrated on their own. See [https://zenodo.org/record/3950379#.XxZ-aFVKipp](https://zenodo.org/record/3950379#.XxZ-aFVKipp)
-
-### Data Instances
-
-
-An example of 'train' looks as follows.
-
-```
-{
-  'id': '0', 
-  'text': 'PLACEHOLDER TEXT', 
-  'subtask_a': 1, 
-}
-```
-
-
-### Data Fields
-
-- `id`: a `string` feature.
-- `text`: a `string`.
-- `subtask_a`: whether or not the instance is offensive; `0: NOT, 1: OFF`
-
-
-### Data Splits
-
-|  name   |train|test|
-|---------|----:|---:|
-|ar|7839|1827|
-|da|2961|329|
-|en|0|3887|
-|gr|8743|1544|
-|tr|31277|3515|
-
-## Dataset Creation
-
-### Curation Rationale
-
-Collecting data for abusive language classification. Different rational for each dataset.
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-Varies per language dataset
-
-#### Who are the source language producers?
-
-Social media users
-
-### Annotations
-
-#### Annotation process
-
-Varies per language dataset
-
-#### Who are the annotators?
-
-Varies per language dataset; native speakers
-
-### Personal and Sensitive Information
-
-The data was public at the time of collection. No PII removal has been performed.
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-The data definitely contains abusive language. The data could be used to develop and propagate offensive language against every target group involved, i.e. ableism, racism, sexism, ageism, and so on.
-
-### Discussion of Biases
-
-
-### Other Known Limitations
-
-
-## Additional Information
-
-### Dataset Curators
-
-The datasets is curated by each sub-part's paper authors.
-
-### Licensing Information
-
-This data is available and distributed under Creative Commons attribution license, CC-BY 4.0. 
-
-### Citation Information
-
-```
-@inproceedings{zampieri-etal-2020-semeval,
-    title = "{S}em{E}val-2020 Task 12: Multilingual Offensive Language Identification in Social Media ({O}ffens{E}val 2020)",
-    author = {Zampieri, Marcos  and
-      Nakov, Preslav  and
-      Rosenthal, Sara  and
-      Atanasova, Pepa  and
-      Karadzhov, Georgi  and
-      Mubarak, Hamdy  and
-      Derczynski, Leon  and
-      Pitenis, Zeses  and
-      {\c{C}}{\"o}ltekin, {\c{C}}a{\u{g}}r{\i}},
-    booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
-    month = dec,
-    year = "2020",
-    address = "Barcelona (online)",
-    publisher = "International Committee for Computational Linguistics",
-    url = "https://aclanthology.org/2020.semeval-1.188",
-    doi = "10.18653/v1/2020.semeval-1.188",
-    pages = "1425--1447",
-    abstract = "We present the results and the main findings of SemEval-2020 Task 12 on Multilingual Offensive Language Identification in Social Media (OffensEval-2020). The task included three subtasks corresponding to the hierarchical taxonomy of the OLID schema from OffensEval-2019, and it was offered in five languages: Arabic, Danish, English, Greek, and Turkish. OffensEval-2020 was one of the most popular tasks at SemEval-2020, attracting a large number of participants across all subtasks and languages: a total of 528 teams signed up to participate in the task, 145 teams submitted official runs on the test data, and 70 teams submitted system description papers.",
-}
-
-```
-
-
-### Contributions
-
-Author-added dataset [@leondz](https://github.com/leondz) 

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The languages included in OffensEval 2020 are:\n\n* Arabic\n* Danish\n* English\n* Greek\n* Turkish\n\nThe annotation follows the hierarchical tagset proposed in the Offensive Language Identification Dataset (OLID) and used in OffensEval 2019. \nIn this taxonomy we break down offensive content into the following three sub-tasks taking the type and target of offensive content into account. \nThe following sub-tasks were organized:\n\n* Sub-task A - Offensive language identification;\n* Sub-task B - Automatic categorization of offense types;\n* Sub-task C - Offense target identification.\n\nThe English training data isn't included here (the text isn't available and needs rehydration of 9 million tweets; \nsee [https://zenodo.org/record/3950379#.XxZ-aFVKipp](https://zenodo.org/record/3950379#.XxZ-aFVKipp))\n", "citation": "@inproceedings{zampieri-etal-2020-semeval,\n    title = \"{S}em{E}val-2020 Task 12: Multilingual Offensive Language Identification in Social Media ({O}ffens{E}val 2020)\",\n    author = {Zampieri, Marcos  and\n      Nakov, Preslav  and\n      Rosenthal, Sara  and\n      Atanasova, Pepa  and\n      Karadzhov, Georgi  and\n      Mubarak, Hamdy  and\n      Derczynski, Leon  and\n      Pitenis, Zeses  and\n      Coltekin, Cagri,\n    booktitle = \"Proceedings of the Fourteenth Workshop on Semantic Evaluation\",\n    month = dec,\n    year = \"2020\",\n    address = \"Barcelona (online)\",\n    publisher = \"International Committee for Computational Linguistics\",\n    url = \"https://aclanthology.org/2020.semeval-1.188\",\n    doi = \"10.18653/v1/2020.semeval-1.188\",\n    pages = \"1425--1447\",\n}\n", "homepage": "https://sites.google.com/site/offensevalsharedtask/results-and-paper-submission", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "original_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "subtask_a": {"num_classes": 2, "names": ["NOT", "OFF"], "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "offens_eval2020", "config_name": "tr", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 4684302, "num_examples": 31277, "dataset_name": "offens_eval2020"}, "test": {"name": "test", "num_bytes": 525706, "num_examples": 3515, "dataset_name": "offens_eval2020"}}, "download_checksums": {"offenseval-tr-training-v1.tsv": {"num_bytes": 4101728, "checksum": "8509c01c4bf387d9e387c4637829585431cc045adaf7d0413c0022bf2bcd4baa"}, "offenseval-tr-labela-v1.csv": {"num_bytes": 35280, "checksum": "ae9b0837e948c3d9c3a147d2a415989a4940a7756d5821b3289276574941c9e3"}, "offenseval-tr-test-v1.tsv": {"num_bytes": 449553, "checksum": "9052784e13248e58658e34a4f86a3463ef8b2594d2feb289e4b29bba2866b437"}}, "download_size": 4586561, "post_processing_size": null, "dataset_size": 5210008, "size_in_bytes": 9796569}}

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offenseval_2020.py

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-# coding=utf-8
-# Copyright 2022 Leon Derczynski.
-#
-# 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
-"""OffensEval 2020: Multilingual Offensive Language Detection"""
-
-import csv
-import os
-
-import datasets
-
-
-logger = datasets.logging.get_logger(__name__)
-
-
-_CITATION = """\
-@inproceedings{zampieri-etal-2020-semeval,
-    title = "{S}em{E}val-2020 Task 12: Multilingual Offensive Language Identification in Social Media ({O}ffens{E}val 2020)",
-    author = {Zampieri, Marcos  and
-      Nakov, Preslav  and
-      Rosenthal, Sara  and
-      Atanasova, Pepa  and
-      Karadzhov, Georgi  and
-      Mubarak, Hamdy  and
-      Derczynski, Leon  and
-      Pitenis, Zeses  and
-      Coltekin, Cagri,
-    booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
-    month = dec,
-    year = "2020",
-    address = "Barcelona (online)",
-    publisher = "International Committee for Computational Linguistics",
-    url = "https://aclanthology.org/2020.semeval-1.188",
-    doi = "10.18653/v1/2020.semeval-1.188",
-    pages = "1425--1447",
-}
-"""
-
-_DESCRIPTION = """\
-OffensEval 2020 features a multilingual dataset with five languages. The languages included in OffensEval 2020 are:
-
-* Arabic
-* Danish
-* English
-* Greek
-* Turkish
-
-The annotation follows the hierarchical tagset proposed in the Offensive Language Identification Dataset (OLID) and used in OffensEval 2019. 
-In this taxonomy we break down offensive content into the following three sub-tasks taking the type and target of offensive content into account. 
-The following sub-tasks were organized:
-
-* Sub-task A - Offensive language identification;
-* Sub-task B - Automatic categorization of offense types;
-* Sub-task C - Offense target identification.
-
-The English training data isn't included here (the text isn't available and needs rehydration of 9 million tweets; 
-see [https://zenodo.org/record/3950379#.XxZ-aFVKipp](https://zenodo.org/record/3950379#.XxZ-aFVKipp))
-"""
-
-# _URL = ""
-
-
-class OffensEval2020Config(datasets.BuilderConfig):
-    """BuilderConfig for OffensEval2020"""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig OffensEval2020.
-
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(OffensEval2020Config, self).__init__(**kwargs)
-
-
-class OffensEval2020(datasets.GeneratorBasedBuilder):
-    """OffensEval2020 dataset."""
-
-    BUILDER_CONFIGS = [
-        OffensEval2020Config(name="ar", version=datasets.Version("1.0.0"), description="Offensive language data in Arabic"),
-        OffensEval2020Config(name="da", version=datasets.Version("1.0.0"), description="Offensive language data in Danish"),
-        OffensEval2020Config(name="en", version=datasets.Version("1.0.0"), description="Offensive language data in English"),
-        OffensEval2020Config(name="gr", version=datasets.Version("1.0.0"), description="Offensive language data in Greek"),
-        OffensEval2020Config(name="tr", version=datasets.Version("1.0.0"), description="Offensive language data in Turkish"),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "original_id": datasets.Value("string"),
-                    "text": datasets.Value("string"),
-                    "subtask_a": datasets.features.ClassLabel(
-                        names=[
-                            "NOT",
-                            "OFF",
-                        ]
-                    ),
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://sites.google.com/site/offensevalsharedtask/results-and-paper-submission",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        train_text   = dl_manager.download_and_extract(f"offenseval-{self.config.name}-training-v1.tsv")
-        test_labels  = dl_manager.download_and_extract(f"offenseval-{self.config.name}-labela-v1.csv")
-        test_text    = dl_manager.download_and_extract(f"offenseval-{self.config.name}-test-v1.tsv")
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_text, "split": 'train'}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": {'labels':test_labels, 'text':test_text}, "split": 'test'}),
-        ]
-
-    def _generate_examples(self, filepath, split=None):
-        if split == "train":
-            logger.info("⏳ Generating examples from = %s", filepath)
-            with open(filepath, encoding="utf-8") as f:
-                OffensEval2020_reader = csv.DictReader(f, delimiter="\t", quotechar='"')
-                guid = 0
-                for instance in OffensEval2020_reader:
-                    instance["text"] = instance.pop("tweet")
-                    instance["original_id"] = instance.pop("id")
-                    instance["id"] = str(guid)
-                    yield guid, instance
-                    guid += 1
-        elif split == 'test':
-            logger.info("⏳ Generating examples from = %s", filepath['text'])
-            labeldict = {}
-            with open(filepath['labels']) as labels:
-                for line in labels:
-                    line = line.strip().split(',')
-                    if line:
-                        labeldict[line[0]] = line[1]
-            with open(filepath['text']) as f:
-                OffensEval2020_reader = csv.DictReader(f, delimiter="\t", quotechar='"')
-                guid = 0
-                for instance in OffensEval2020_reader:
-                    instance["text"] = instance.pop("tweet")
-                    instance["original_id"] = instance.pop("id")
-                    instance["id"] = str(guid)
-                    instance["subtask_a"] = labeldict[instance["original_id"]]
-                    yield guid, instance
-                    guid += 1
-

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