added data loading script and dataset card

README.md

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+---
+annotations_creators:
+- machine-generated
+language:
+- fa
+- ru
+- zh
+language_creators:
+- machine-generated
+multilinguality:
+- multilingual
+pretty_name: NeuMARCO
+size_categories:
+- 1M<n<10M
+source_datasets:
+- extended|irds/msmarco-passage
+tags: []
+task_categories:
+- text-retrieval
+---
+
+# Dataset Card for NeuMARCO
+
+## Dataset Description
+
+- **Website:** https://neuclir.github.io/
+
+### Dataset Summary
+
+This is the dataset created for TREC 2022 NeuCLIR Track. The collection consists of documents from [`msmarco-passage`](ir-datasets.com/msmarco-passage) translated into
+Chinese, Persian, and Russian.
+
+### Languages
+
+ - Chinese
+ - Persian
+ - Russian
+
+## Dataset Structure
+
+### Data Instances
+
+| Split           | Documents |
+|-----------------|----------:|
+| `fas` (Persian) |      8.8M |
+| `rus` (Russian) |      8.8M |
+| `zho` (Chinese) |      8.8M |
+
+### Data Fields
+ - `doc_id`: unique identifier for this document
+ - `text`: translated passage text
+
+## Dataset Usage
+
+Using 🤗 Datasets:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset('neuclir/neumarco')
+dataset['fas'] # Persian passages
+dataset['rus'] # Russian passages
+dataset['zho'] # Chinese passages
+```

neumarco.py

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+import tarfile
+import os
+import datasets
+
+_URL = "https://huggingface.co/datasets/neuclir/neumarco/resolve/main/data/neumarco.tar.gz"
+
+
+class Neumarco(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            features=datasets.Features({
+              "doc_id": datasets.Value("string"),
+              "text": datasets.Value("string"),
+            }),
+        )
+
+    def _split_generators(self, dl_manager):
+        path = dl_manager.download(_URL)
+        return [
+            datasets.SplitGenerator(
+                name=lang,
+                gen_kwargs={
+                    "filepath": path,
+                    "tarpath": f'eng-{lang}/msmarco.collection.20210731-scale21-sockeye2-tm1.tsv'
+                })
+            for lang in ['fas', 'rus', 'zho']
+        ]
+
+    def _generate_examples(self, filepath, tarpath):
+        with tarfile.open(filepath, 'r|gz') as tarf:
+            for fileinfo in tarf:
+                if fileinfo.name != tarpath:
+                    continue
+                with tarf.extractfile(fileinfo) as f:
+                    for key, line in enumerate(f):
+                        doc_id, text = line.decode('utf8').rstrip('\n').split('\t')
+                        yield key, {'doc_id': doc_id, 'text': text}
+                break