Several
Browse files- Naija-Lexicons.py +149 -0
- dataset_infos.json +56 -0
Naija-Lexicons.py
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# coding=utf-8
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""NaijaSenti: A Nigerian Twitter Sentiment Corpus for Multilingual Sentiment Analysis"""
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_HOMEPAGE = "https://github.com/hausanlp/NaijaSenti"
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_DESCRIPTION = """\
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Naija-Stopwords is a part of the Naija-Senti project. It is a list of collected stopwords from the four most widely spoken languages in Nigeria — Hausa, Igbo, Nigerian-Pidgin, and Yorùbá.
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"""
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_CITATION = """\
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@inproceedings{muhammad-etal-2022-naijasenti,
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title = "{N}aija{S}enti: A {N}igerian {T}witter Sentiment Corpus for Multilingual Sentiment Analysis",
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author = "Muhammad, Shamsuddeen Hassan and
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Adelani, David Ifeoluwa and
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Ruder, Sebastian and
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Ahmad, Ibrahim Sa{'}id and
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Abdulmumin, Idris and
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Bello, Bello Shehu and
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Choudhury, Monojit and
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Emezue, Chris Chinenye and
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Abdullahi, Saheed Salahudeen and
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Aremu, Anuoluwapo and
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Jorge, Al{\'\i}pio and
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Brazdil, Pavel",
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booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
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month = jun,
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year = "2022",
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address = "Marseille, France",
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publisher = "European Language Resources Association",
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url = "https://aclanthology.org/2022.lrec-1.63",
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pages = "590--602",
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}
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"""
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import textwrap
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import pandas as pd
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import datasets
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LANGUAGES = ['hausa', 'igbo', 'yoruba']
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class NaijaLexiconsConfig(datasets.BuilderConfig):
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"""BuilderConfig for NaijaLexicons"""
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def __init__(
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self,
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text_features,
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label_column,
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label_classes,
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manual_url,
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translated_url,
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citation,
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**kwargs,
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):
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"""BuilderConfig for NaijaLexicons.
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Args:
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text_features: `dict[string]`, map from the name of the feature
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dict for each text field to the name of the column in the txt/csv/tsv file
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label_column: `string`, name of the column in the txt/csv/tsv file corresponding
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to the label
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label_classes: `list[string]`, the list of classes if the label is categorical
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train_url: `string`, url to train file from
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valid_url: `string`, url to valid file from
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test_url: `string`, url to test file from
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citation: `string`, citation for the data set
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**kwargs: keyword arguments forwarded to super.
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"""
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super(NaijaLexiconsConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
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self.text_features = text_features
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self.label_column = label_column
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self.label_classes = label_classes
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self.manual_url = manual_url
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self.translated_url = translated_url
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self.citation = citation
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class NaijaLexicons(datasets.GeneratorBasedBuilder):
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"""NaijaLexicons benchmark"""
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BUILDER_CONFIGS = []
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for lang in LANGUAGES:
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BUILDER_CONFIGS.append(
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NaijaLexiconsConfig(
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name=lang,
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description=textwrap.dedent(
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f"""{_DESCRIPTION}"""
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),
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text_features={"word": "word"},
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label_classes=["positive", "negative"],
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label_column="label",
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manual_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/sentiment-lexicons/manual/{lang}/mixed.csv",
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translated_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/sentiment-lexicons/translated/{lang}/mixed.csv",
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citation=textwrap.dedent(
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f"""{_CITATION}"""
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),
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),
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)
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def _info(self):
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features = {text_feature: datasets.Value("string") for text_feature in self.config.text_features}
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features["label"] = datasets.features.ClassLabel(names=self.config.label_classes)
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return datasets.DatasetInfo(
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description=self.config.description,
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features=datasets.Features(features),
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citation=self.config.citation,
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)
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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manual_path = dl_manager.download_and_extract(self.config.manual_url)
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translated_path = dl_manager.download_and_extract(self.config.translated_url)
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return [
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datasets.SplitGenerator(name='words', gen_kwargs={"filepath": manual_path}),
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datasets.SplitGenerator(name='words', gen_kwargs={"filepath": translated_path})
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]
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def _generate_examples(self, filepath):
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df = pd.read_csv(filepath)
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print('-'*100)
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print(df.head())
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print('-'*100)
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for id_, row in df.iterrows():
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word = row["word"]
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label = row["label"]
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yield id_, {"word": word, "label": label}
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dataset_infos.json
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@@ -0,0 +1,56 @@
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{
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"default": {
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"description": "Naija-Lexicons is a part of the Naija-Senti project. It is a list of collected stopwords from the four most widely spoken languages in Nigeria — Hausa, Igbo, Nigerian-Pidgin, and Yorùbá.\n",
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"citation": " ",
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"homepage": "https://github.com/hausanlp/NaijaSenti",
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"license": "",
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"features": {
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"word": {
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"dtype": "string",
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"id": null,
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"_type": "Value"
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},
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"label": {
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"num_classes": 2,
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"names": [
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"positive",
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"negative"
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],
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"names_file": null,
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"id": null,
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"_type": "ClassLabel"
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}
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},
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"post_processed": null,
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"supervised_keys": {
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"input": "word",
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"output": "label"
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},
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"task_templates": [
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{
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"task": "text-classification",
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"text_column": "word",
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"label_column": "label",
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"labels": [
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"positive",
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"negative",
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"neutral"
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]
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}
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],
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"builder_name": "NaijaLexicons",
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"config_name": "default",
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"version": {
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"version_str": "0.0.0",
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"description": null,
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"major": 0,
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"minor": 0,
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"patch": 0
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},
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"download_size": 2069616,
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"post_processing_size": null,
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"dataset_size": 2173417,
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"size_in_bytes": 4243033
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}
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}
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