Upload with huggingface_hub

MANIFEST.sha256

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+a5d05e8ad6e18b797d5c71fe03c317ffeeab289404f0db0d635ff7e021da5c5c  README.md
+d69d22d439f0f1eb1f82b197fb2695e708660b8f0da66e7334a198629259faf5  data/corpus/corpus.jsonl
+ed06dae52c96c84c662714a5adb6a7f23d740937c37b2a89867a97fffeb99786  data/default/dev.jsonl
+6a196337d7f156f260e181841a125c78d998f115b48de4d50c365d2e7646a05f  data/default/test.jsonl
+5f4767e04e3d7ae589cb3f8fa2866b2b033ede42838397f485abb3d317834fc7  data/queries/dev.jsonl
+51d4bb5f7ab10678b5a618a27bf6103aaacc49fdaa277d6c12fd0cee701a87cf  data/queries/test.jsonl
+8f27cf4b7281ece34585abf969b6dcb76c8ab719dea80b3b0d16fdae20d58643  dataset_statistics.json

README.md

@@ -1,3 +1,84 @@
 ---
-license: apache-2.0
+language:
+- en
+license: other
+license_name: github-terms-of-service
+task_categories:
+- question-answering
+- information-retrieval
+tags:
+- rag
+- github-issues
+- cross-issue-reasoning
+- silver-labels
+pretty_name: MetaRAG Cross-Issue OSSQA
+size_categories:
+- 10K<n<100K
+configs:
+- config_name: default
+  default: true
+  data_files:
+  - split: dev
+    path: data/default/dev.jsonl
+  - split: test
+    path: data/default/test.jsonl
+- config_name: queries
+  data_files:
+  - split: dev
+    path: data/queries/dev.jsonl
+  - split: test
+    path: data/queries/test.jsonl
+- config_name: corpus
+  data_files:
+  - split: corpus
+    path: data/corpus/corpus.jsonl
 ---
+
+# MetaRAG Cross-Issue OSSQA
+
+MetaRAG Cross-Issue OSSQA is an English open-source software issue question-answering and retrieval benchmark. Each example asks a question grounded in one GitHub issue and requires evidence from a related issue. The data contains explicit cross-issue references and a three-document silver evidence path.
+
+## Dataset configurations
+
+| Configuration | Splits | Rows | Purpose |
+| --- | --- | ---: | --- |
+| `default` | `dev`, `test` | 100 / 400 | Complete evaluation records, including embedded issue fragments and silver labels. |
+| `queries` | `dev`, `test` | 100 / 400 | Retrieval and QA queries with answer and evidence-path supervision. |
+| `corpus` | `corpus` | 9,536 | Deduplicated issue-description and issue-comment fragments for retrieval. This is a knowledge corpus, not a training split. |
+
+## Loading
+
+```python
+from datasets import load_dataset
+
+evaluation = load_dataset("<namespace>/metarag-cross-issue-ossqa")
+queries = load_dataset("<namespace>/metarag-cross-issue-ossqa", "queries")
+corpus = load_dataset("<namespace>/metarag-cross-issue-ossqa", "corpus", split="corpus")
+```
+
+## Main fields
+
+`default` includes the query, its known context, answer, source and target issue metadata, `silver_evidence_path`, quality signals, and the ordered `fragments` supporting each example. `queries` is the compact query-level representation. `corpus` contains one searchable fragment per `document_id`, plus issue, repository, author, timestamp, and cross-issue-link metadata.
+
+The fields `answer_document_id` and `silver_evidence_path` refer to `corpus.document_id`. `known_context_document_ids` identifies documents supplied as query context; these are excluded from the gold evidence path. `split` is repository-disjoint between `dev` and `test`.
+
+## Data creation
+
+The dataset was constructed from public GitHub event data via OpenDigger / GH Archive, from 2022-01-01 through 2025-12-31. It contains 500 qualified cross-issue samples from 468 repositories. The sampling procedure requires an explicit cross-issue reference, a path spanning at least two distinct issues, English-language filtering, deterministic diversity sampling, and repository-disjoint development/test partitions.
+
+See `dataset_statistics.json` for the complete sampling settings, quality distribution, year distribution, and leakage audit result.
+
+## Labels and limitations
+
+`reference_answer` and `silver_evidence_path` are heuristic silver annotations. They should not be treated as human-validated gold labels without additional review. Source text may contain stale links, personal identifiers visible in public GitHub content, inaccurate technical claims, or other artifacts of public issue discussions.
+
+The data is intended for research and evaluation. Users are responsible for ensuring their use complies with the applicable [GitHub Terms of Service](https://docs.github.com/en/site-policy/github-terms/github-terms-of-service), the source platforms' policies, and their own privacy, legal, and ethical requirements.
+
+## Provenance
+
+- OpenDigger: <https://github.com/X-lab2017/open-digger>
+- GH Archive: <https://www.gharchive.org/>
+
+## Repository integrity
+
+`MANIFEST.sha256` contains SHA-256 checksums for every data file and `dataset_statistics.json` in this package. To regenerate the package from the accompanying source files, remove this output directory and run `python3 prepare_hf_dataset.py`.

dataset_statistics.json

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+{
+  "generated_at": "2026-08-19T16:47:49.148769",
+  "source": "OpenDigger / GH Archive public GitHub event log",
+  "database": "opensource",
+  "time_range": {
+    "start": "2022-01-01",
+    "end_exclusive": "2026-01-01"
+  },
+  "candidate_issue_count": 28105,
+  "qualified_before_diversity": 950,
+  "final_sample_count": 500,
+  "repository_count": 468,
+  "corpus_fragment_count": 9536,
+  "random_seed": 20260820,
+  "sampling_strategy": "explicit-reference cross-issue qualification followed by year-quality stratified deterministic random round-robin",
+  "path_length_distribution": {
+    "3": 500
+  },
+  "sample_year_distribution": {
+    "2016": 2,
+    "2017": 3,
+    "2018": 3,
+    "2019": 2,
+    "2020": 9,
+    "2021": 38,
+    "2022": 116,
+    "2023": 121,
+    "2024": 111,
+    "2025": 95
+  },
+  "split_distribution": {
+    "dev": 100,
+    "test": 400
+  },
+  "cross_repository_sample_count": 105,
+  "cross_issue_sample_count": 500,
+  "leakage_audit_violations": 0,
+  "quality_score": {
+    "minimum": 70.0,
+    "maximum": 96.0,
+    "mean": 88.919,
+    "median": 88.0
+  },
+  "valid_comments_per_sample": {
+    "minimum": 3,
+    "maximum": 250,
+    "mean": 17.072
+  },
+  "top_repositories": [
+    [
+      "microsoft/vscode",
+      8
+    ],
+    [
+      "flutter/flutter",
+      5
+    ],
+    [
+      "quarkusio/quarkus",
+      3
+    ],
+    [
+      "microsoft/TypeScript",
+      3
+    ],
+    [
+      "godotengine/godot",
+      3
+    ],
+    [
+      "python/cpython",
+      2
+    ],
+    [
+      "WordPress/gutenberg",
+      2
+    ],
+    [
+      "home-assistant/core",
+      2
+    ],
+    [
+      "vmware-tanzu/velero",
+      2
+    ],
+    [
+      "FlutterFlow/flutterflow-issues",
+      2
+    ],
+    [
+      "wagtail/wagtail",
+      2
+    ],
+    [
+      "sourcegraph/cody",
+      2
+    ],
+    [
+      "open-telemetry/opentelemetry-collector-contrib",
+      2
+    ],
+    [
+      "apache/shardingsphere",
+      2
+    ],
+    [
+      "rails/rails",
+      2
+    ],
+    [
+      "microsoft/vscode-cpptools",
+      2
+    ],
+    [
+      "llvm/llvm-project",
+      2
+    ],
+    [
+      "darthcloud/BlueRetro",
+      2
+    ],
+    [
+      "dotnet/maui",
+      2
+    ],
+    [
+      "gitpod-io/gitpod",
+      2
+    ]
+  ],
+  "selection_rules": {
+    "target_samples": 500,
+    "candidate_pool_size": 30000,
+    "minimum_quality_score": 62.0,
+    "max_samples_per_repository": 8,
+    "maintainer_associations": [
+      "COLLABORATOR",
+      "MEMBER",
+      "OWNER"
+    ],
+    "english_only": true,
+    "minimum_english_ratio": 0.65,
+    "random_seed": 20260820,
+    "explicit_reference_required": true,
+    "minimum_distinct_issue_ids_in_path": 2,
+    "known_query_context_excluded_from_gold_path": true,
+    "repository_disjoint_dev_test_split": true
+  },
+  "annotation_notice": "reference_answer and silver_evidence_path are heuristic silver labels. Human validation is required before reporting gold path metrics."
+}

upload_to_huggingface.py

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+from pathlib import Path
+
+from huggingface_hub import login, upload_folder
+
+
+REPO_ID = "MapleBi/MetaRAG_Cross-Issue_OSSQA"
+DATASET_FOLDER = Path(__file__).resolve().parent
+
+
+def main() -> None:
+    login()
+    upload_folder(
+        folder_path=str(DATASET_FOLDER),
+        repo_id=REPO_ID,
+        repo_type="dataset",
+    )
+
+
+if __name__ == "__main__":
+    main()