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README.md

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----
-language: 
-  - af
-  - am
-  - arz
-  - ha
-  - ig
-  - ary
-  - nso
-  - sn
-  - so
-  - sw
-  - ti
-  - tw
-  - wo
-  - yo
-  - zu
-
-    
-multilinguality:
-  - multilingual   
-   
-task_categories:
-  - text-retrieval
-license: apache-2.0
-
-viewer: true
----
-
-# Dataset Summary
-AfriCLIRMatrix is a test collection for cross-lingual information retrieval research in 15 diverse African languages. This resource comprises English queries with query–document relevance judgments in 15 African languages automatically mined from Wikipedia
-
-This dataset stores documents of AfriCLIRMatrix. To access the queries and judgments, please refer to [castorini/africlirmatrix](https://github.com/castorini/africlirmatrix).
-
-# Dataset Structure
-The only configuration here is the `language`.
-
-An example of document data entry looks as follows:
-```
-{
-  'id': '62443', 
-  'contents': 'Acyloin condensation jẹ́ ìyọkúrò àsopọ̀ àwọn carboxylic ester pẹ̀lú lílò metalic sodium lati ṣèdá α-hydroxyketone, tí wọ́n tún mọ̀ sí. Àdàpọ̀ ṣisẹ́ yìí jẹ́ èyí tó ...'
-}
-
-```
-# Load Dataset
-An example to load the dataset:
-```
-language = 'yoruba'
-dataset = load_dataset('castorini/africlirmatrix', language, 'train')
-```
-# Citation Information
-
-```
-coming soon
-```

africlirmatrix.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.
-
-# Lint as: python3
-
-import json
-
-import datasets
-from dataclasses import dataclass
-
-_CITATION = '''
-coming soon ...
-'''
-
-languages = [
-    'afrikaans',
-    'amharic',
-    'egyptian_arabic',
-    'hausa',
-    'igbo',
-    'moroccan_arabic',
-    'northern_sotho',
-    'shona',
-    'somali',
-    'swahili',
-    'tigrinya',
-    'twi',
-    'wolof',
-    'yoruba',
-    'zulu'
-]
-
-_DESCRIPTION = 'dataset load script for AfriClirMatrix'
-
-_DATASET_URLS = {
-    lang: {
-        'train': f'https://huggingface.co/datasets/ToluClassics/africlirmatrix/resolve/main/africlirmatrix-v1.0-{lang}/corpus.jsonl',
-    } for lang in languages
-}
-
-
-class MrTyDiCorpus(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            version=datasets.Version('1.1.0'),
-            name=lang, 
-            description=f'AfriCLIRMatrix dataset in language {lang}.'
-        ) for lang in languages
-    ]
-
-    def _info(self):
-        features = datasets.Features({
-            'id': datasets.Value('string'), 
-            'contents': datasets.Value('string'),
-        })
-
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # This defines the different columns of the dataset and their types
-            features=features,  # Here we define them above because they are different between the two configurations
-            supervised_keys=None,
-            # Homepage of the dataset for documentation
-            homepage='https://github.com/castorini/africlirmatrix',
-            # License for the dataset if available
-            license='',
-            # Citation for the dataset
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        lang = self.config.name
-        downloaded_files = dl_manager.download_and_extract(_DATASET_URLS[lang])
-
-        splits = [
-            datasets.SplitGenerator(
-                name='train',
-                gen_kwargs={
-                    'filepath': downloaded_files['train'],
-                },
-            ),
-        ]
-        return splits
-
-    def _generate_examples(self, filepath):
-        with open(filepath, encoding="utf-8") as f:
-            for line in f:
-                data = json.loads(line)
-                yield data['id'], data

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