Update README.md

README.md

@@ -22,19 +22,54 @@ dataset_info:
     - name: test
 ---
 
-# DRCD for Document Retrieval (Simplified Chinese)
+ DRCD for Document Retrieval (Simplified Chinese)
 
-This dataset is a reformatted version of the [Delta Reading Comprehension Dataset (DRCD)](https://github.com/DRCKnowledgeTeam/DRCD), converted to Simplified Chinese and adapted for **document retrieval** tasks.
+This dataset is a reformatted version of the [Delta Reading Comprehension Dataset (DRCD)](https://github.com/DRCKnowledgeTeam/DRCD), converted to Simplified Chinese and adapted for **document-level retrieval** tasks.
 
 ## Summary
 
-The dataset transforms the original DRCD QA data into a passage retrieval setup commonly used in open-domain question answering. It is suitable for training and evaluating sparse/dense retrievers such as BM25, DPR, or ColBERT.
+The dataset transforms the original DRCD QA data into a **document retrieval** setting, where queries are used to retrieve **entire Wikipedia articles** rather than individual passages. Each document is the full text of a Wikipedia entry.
+
+The format is compatible with the data structure used in the **[LongEmbed benchmark](https://github.com/THU-KEG/LongEmbed)** and can be directly plugged into LongEmbed evaluation or training pipelines.
 
 ## Key Features
 
-- 🔤 **Language**: Simplified Chinese (converted from Traditional)
-- 📚 **Domain**: General Wikipedia
-- 🔍 **Use Cases**: Passage retrieval, open-domain QA, reranking, dense/sparse IR
+- 🔤 **Language**: Simplified Chinese (converted from Traditional Chinese)
+- 📚 **Domain**: General domain, from Wikipedia
+- 📄 **Granularity**: **Full-document retrieval**, not passage-level
+- 🔍 **Use Cases**: Long-document retrieval, reranking, open-domain QA pre-retrieval
+
+## File Structure
+
+### `corpus.jsonl`
+
+Each line is a single Wikipedia article in Simplified Chinese.
+
+```json
+{"id": "doc_00001", "title": "心理", "text": "心理学是一门研究人类和动物的心理现象、意识和行为的科学。..."}
+```
+
+### `queries.jsonl`
+
+Each line is a user query (from the DRCD question field).
+
+{"qid": "6513-4-1", "text": "威廉·冯特为何被誉为“实验心理学之父”?"}
+
+### `qrels.jsonl`
+
+Standard relevance judgments mapping queries to relevant documents.
+
+``` json
+{"qid": "6513-4-1", "doc_id": "6513"}
+```
+
+This structure matches [LongEmbed Benchmark](https://github.com/dwzhu-pku/LongEmbed)'s data format, making it suitable for evaluating long-document retrievers out of the box.
+
+## Example: Document Retrieval Using BM25
+
+You can quickly try out document-level retrieval using BM25 with the following code snippet:
+
+<Placeholder>
 
 ## License
 The dataset is distributed under the Creative Commons Attribution-ShareAlike 3.0 License (CC BY-SA 3.0). You must give appropriate credit and share any derivative works under the same terms.