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license: apache-2.0
---
---
license: apache-2.0
task_categories:
- document-understanding
- text-generation
language:
- en
---
README.md
train.jsonl
val.jsonl
test.jsonl
{"instruction":"Extract payment amount and due date from the document","input":"Invoice #1029. Total payable amount is $5,000 due by January 30, 2025.","output":"{\"amount\":\"$5,000\",\"due_date\":\"2025-01-30\"}"}
{"instruction":"Identify potential risks in the contract","input":"Payment shall be made within 90 days. No penalty clause is specified.","output":"{\"risk\":\"Delayed payment risk\"}"}
{"instruction":"Extract key entities from the agreement","input":"The client agrees to pay USD 12,000 upon project completion.","output":"{\"amount\":\"$12,000\"}"}
{"instruction":"Classify the document section","input":"Termination clause: Either party may terminate with 30 days notice.","output":"{\"section\":\"Termination\"}"}
# DocuMind ERNIE 4.5 Document Reasoning Dataset
Instruction-style dataset for fine-tuning ERNIE 4.5 on OCR-based document
understanding and reasoning tasks.
## Data Source
Documents are processed using PaddleOCR-VL to extract text and layout.
Data is anonymized and partially synthetic.
## Schema
Each record:
{
"instruction": "...",
"input": "<OCR extracted document text>",
"output": "<structured JSON>"
}
## Tasks
- Entity extraction
- Risk identification
- Section classification
- Contract reasoning
## Splits
- train.jsonl
- val.jsonl
- test.jsonl
## License
Apache-2.0
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