Upload 2 files

LICENSE

@@ -0,0 +1,5 @@
+Apache License
+Version 2.0, January 2004
+
+This repository ships a template dataset package.
+For the full Apache-2.0 text, see: https://www.apache.org/licenses/LICENSE-2.0

README.md

@@ -0,0 +1,66 @@
+---
+pretty_name: CitationGround-1M (Platinum)
+language:
+- en
+license: apache-2.0
+task_categories:
+- question-answering
+- text-generation
+tags:
+- rag
+- grounding
+- citations
+- retrieval
+- hallucination-reduction
+- hard-negatives
+size_categories:
+- n<1K  # sample pack; replace after scaling
+dataset_info:
+  creator: "Within US AI"
+  contact: "Within US AI"
+  created: "2025-12-30T16:53:41Z"
+  schema: "See Features section below"
+---
+
+# CitationGround-1M (Platinum)
+
+**Developer/Publisher:** Within US AI  
+**Version:** 0.1.0 (sample pack)  
+**Created:** 2025-12-30T16:53:41Z
+
+## What this dataset is
+`CitationGround-1M` is a **citation-locked** grounded QA/RAG dataset:
+- Answer using only the provided `contexts`
+- Provide **span-level citations** (doc_id + offsets)
+- Includes `answerable=false` hard negatives for abstention behavior
+
+## Features / schema (JSONL)
+- `example_id` (string)
+- `question` (string)
+- `contexts` (list of docs)
+- `answer` (string)
+- `citations` (list of spans)
+- `answerable` (bool)
+- `difficulty` (int; 1–5)
+- `reason` (string)
+- `language` (string)
+- `created_utc` (string)
+- `license_note` (string)
+
+### Context doc format
+- `doc_id`, `title`, `text`, `source_type`, `provenance`
+
+### Citation span format
+- `doc_id`, `start`, `end` (character offsets in `text`)
+
+## Splits
+- `data/train.jsonl`
+- `data/validation.jsonl`
+- `data/test.jsonl`
+
+## How to load
+```python
+from datasets import load_dataset
+ds = load_dataset("json", data_files={"train":"data/train.jsonl","validation":"data/validation.jsonl","test":"data/test.jsonl"})
+print(ds["train"][0])
+```