First commit

Naija-Stopwords.py

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+# coding=utf-8
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# 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.
+"""NaijaSenti: A Nigerian Twitter Sentiment Corpus for Multilingual Sentiment Analysis"""
+
+
+
+_HOMEPAGE = "https://github.com/hausanlp/NaijaSenti"
+
+_DESCRIPTION = """\
+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.
+"""
+
+
+_CITATION = """\
+@inproceedings{muhammad-etal-2022-naijasenti,
+    title = "{N}aija{S}enti: A {N}igerian {T}witter Sentiment Corpus for Multilingual Sentiment Analysis",
+    author = "Muhammad, Shamsuddeen Hassan  and
+      Adelani, David Ifeoluwa  and
+      Ruder, Sebastian  and
+      Ahmad, Ibrahim Sa{'}id  and
+      Abdulmumin, Idris  and
+      Bello, Bello Shehu  and
+      Choudhury, Monojit  and
+      Emezue, Chris Chinenye  and
+      Abdullahi, Saheed Salahudeen  and
+      Aremu, Anuoluwapo  and
+      Jorge, Al{\'\i}pio  and
+      Brazdil, Pavel",
+    booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
+    month = jun,
+    year = "2022",
+    address = "Marseille, France",
+    publisher = "European Language Resources Association",
+    url = "https://aclanthology.org/2022.lrec-1.63",
+    pages = "590--602",
+}
+"""
+
+
+import textwrap
+import pandas as pd
+
+import datasets
+
+LANGUAGES = ['hausa', 'igbo', 'yoruba', 'nigerian_pidgin']
+
+class NaijaSentiConfig(datasets.BuilderConfig):
+    """BuilderConfig for NaijaSenti"""
+
+    def __init__(
+        self,
+        text_features,
+        stopwords_url,
+        citation,
+        **kwargs,
+    ):
+        """BuilderConfig for NaijaSenti.
+
+        Args:
+          text_features: `dict[string]`, map from the name of the feature
+            dict for each text field to the name of the column in the txt/csv/tsv file
+          label_column: `string`, name of the column in the txt/csv/tsv file corresponding
+            to the label
+          label_classes: `list[string]`, the list of classes if the label is categorical
+          train_url: `string`, url to train file from
+          valid_url: `string`, url to valid file from
+          test_url: `string`, url to test file from
+          citation: `string`, citation for the data set
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(NaijaSentiConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
+        self.text_features = text_features
+        self.stopwords_url = stopwords_url
+        self.citation = citation
+
+
+class NaijaSenti(datasets.GeneratorBasedBuilder):
+    """NaijaSenti benchmark"""
+
+    BUILDER_CONFIGS = []
+
+    for lang in LANGUAGES:
+        BUILDER_CONFIGS.append(
+            NaijaSentiConfig(
+                name=lang,
+                description=textwrap.dedent(
+                    f"""{_DESCRIPTION}"""
+                ),
+                text_features={"word": "word"},
+                stopwords_url=f"https://raw.githubusercontent.com/hausanlp/NaijaSenti/main/data/stopwords/{lang}_stopwords.csv",
+                citation=textwrap.dedent(
+                    f"""{_CITATION}"""
+                ),
+            ),
+        )
+
+    def _info(self):
+        features = {text_feature: datasets.Value("string") for text_feature in self.config.text_features}
+
+        return datasets.DatasetInfo(
+            description=self.config.description,
+            features=datasets.Features(features),
+            citation=self.config.citation,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        stpowords_path = dl_manager.download_and_extract(self.config.stopwords_url)
+        
+        return [
+            datasets.SplitGenerator(name='stopwords', gen_kwargs={"filepath": stpowords_path})
+        ]
+
+    def _generate_examples(self, filepath):
+        df = pd.read_csv(filepath, sep='\t')
+
+        print('-'*100)
+        print(df.head())
+        print('-'*100)
+
+        for id_, row in df.iterrows():
+            stopword = row["word"]
+
+            yield id_, {"stopword": stopword}

dataset_infos.json

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+{
+  "default": {
+    "description": "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.\n",
+    "citation": " ",
+    "homepage": "https://github.com/afrisenti-semeval/afrisent-semeval-2023",
+    "license": "",
+    "features": {
+      "word": {
+        "dtype": "string",
+        "id": null,
+        "_type": "Value"
+      }
+    },
+    "post_processed": null,
+    "task_templates": [
+      {
+        "task": "text-classification",
+        "word_column": "word"
+      }
+    ],
+    "builder_name": "Naija-Stopwords",
+    "config_name": "default",
+    "version": {
+      "version_str": "0.0.0",
+      "description": null,
+      "major": 0,
+      "minor": 0,
+      "patch": 0
+  
+    },
+    "download_size": 2069616,
+    "post_processing_size": null,
+    "dataset_size": 2173417,
+    "size_in_bytes": 4243033
+  }
+}