init

.gitattributes

@@ -53,3 +53,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+*.jsonl filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+language: 
+  - fas
+  - rus
+  - zho
+
+    
+multilinguality:
+- multilingual    
+
+task_categories:
+- text-retrieval
+
+---
+
+From the NeuCLIR TREC Track 2022: https://arxiv.org/abs/2304.12367
+
+Generated from https://huggingface.co/datasets/neuclir/neuclir1
+
+```
+@article{lawrie2023overview,
+  title={Overview of the TREC 2022 NeuCLIR track},
+  author={Lawrie, Dawn and MacAvaney, Sean and Mayfield, James and McNamee, Paul and Oard, Douglas W and Soldaini, Luca and Yang, Eugene},
+  journal={arXiv preprint arXiv:2304.12367},
+  year={2023}
+}
+```
+

neuclir-2022.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
+
+_CITATION = '''
+@article{lawrie2023overview,
+  title={Overview of the TREC 2022 NeuCLIR track},
+  author={Lawrie, Dawn and MacAvaney, Sean and Mayfield, James and McNamee, Paul and Oard, Douglas W and Soldaini, Luca and Yang, Eugene},
+  journal={arXiv preprint arXiv:2304.12367},
+  year={2023}
+}
+'''
+
+_LANGUAGES = [
+    'rus',
+    'fas',
+    'zho',
+]
+
+_DESCRIPTION = 'dataset load script for NeuCLIR 2022'
+
+_DATASET_URLS = {
+    lang: {
+        'test': f'https://huggingface.co/datasets/MTEB/neuclir-2022/resolve/main/neuclir-{lang}/queries.jsonl.gz',
+    } for lang in _LANGUAGES
+}
+
+_DATASET_CORPUS_URLS = {
+    f'corpus-{lang}': {
+        'corpus': f'https://huggingface.co/datasets/MTEB/neuclir-2022/resolve/main/neuclir-{lang}/corpus.jsonl.gz'
+    } for lang in _LANGUAGES
+}
+
+
+class MLDR(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [datasets.BuilderConfig(
+            version=datasets.Version('1.0.0'),
+            name=lang, description=f'MLDR dataset in language {lang}.'
+        ) for lang in _LANGUAGES
+    ] + [
+        datasets.BuilderConfig(
+            version=datasets.Version('1.0.0'),
+            name=f'corpus-{lang}', description=f'corpus of MLDR dataset in language {lang}.'
+        ) for lang in _LANGUAGES
+    ]
+
+    def _info(self):
+        name = self.config.name
+        if name.startswith('corpus-'):
+            features = datasets.Features({
+                '_id': datasets.Value('string'),
+                'text': datasets.Value('string'),
+            })
+        else:
+            features = datasets.Features({
+                '_id': datasets.Value('string'),
+                'query': 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/FlagOpen/FlagEmbedding',
+            # License for the dataset if available
+            license='mit',
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        name = self.config.name
+        if name.startswith('corpus-'):
+            downloaded_files = dl_manager.download_and_extract(_DATASET_CORPUS_URLS[name])
+            splits = [
+                datasets.SplitGenerator(
+                    name='corpus',
+                    gen_kwargs={
+                        'filepath': downloaded_files['corpus'],
+                    },
+                ),
+            ]
+        else:
+            downloaded_files = dl_manager.download_and_extract(_DATASET_URLS[name])
+            splits = [
+                datasets.SplitGenerator(
+                    name='test',
+                    gen_kwargs={
+                        'filepath': downloaded_files['test'],
+                    },
+                ),
+            ]
+        return splits
+
+    def _generate_examples(self, filepath):
+        name = self.config.name
+        if name.startswith('corpus-'):
+            with open(filepath, encoding='utf-8') as f:
+                for line in f:
+                    data = json.loads(line)
+                    yield data['docid'], data
+        else:
+            with open(filepath, encoding="utf-8") as f:
+                for line in f:
+                    data = json.loads(line)
+                    qid = data['query_id']
+                    yield qid, data

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neuclir-zho/corpus.jsonl

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neuclir-zho/test.jsonl

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