prompts/gpt.md

GPT (OpenAI)

• Runner: scripts/run_gpt.py
• Result set: results/gpt/<doc_id>.json
• Default model: gpt-5.5 (override with OPENAI_MODEL)
• API: OpenAI Responses API (/v1/responses) with Structured Outputs
• Schema mode: openai_strict_nullable_v1

Prompt

The user instruction is loaded from extraction_prompt.txt:

Extract the document into the supplied JSON schema. Use only information present in the
document. Return null for fields that are not printed or cannot be determined. Preserve
table rows as arrays and preserve the document language for values. Document id: {doc_id}.

The document is attached as an input_file (PDF / native files via the Files API), an input_image (JPEG/PNG/WebP/GIF), or a sequence of PNG pages converted from multipage TIFF.

Output constraint

The schema is sent as text.format of type json_schema with strict: true. The raw benchmark schema is first normalized (normalize_output_schema) into OpenAI's strict subset:

• drop $schema, examples, default, title, format, and any x_* keys
• every object lists all properties in required and sets additionalProperties: false
• objects and primitives are made nullable so a labeled null can be returned
• enum literals are sanitized and gain a null member when nullable

Run knobs (environment)

• OPENAI_API_KEY (required)
• OPENAI_MODEL, OPENAI_API_BASE
• OPENAI_MAX_OUTPUT_TOKENS, OPENAI_REASONING_EFFORT
• OPENAI_INPUT_USD_PER_1M, OPENAI_OUTPUT_USD_PER_1M (optional cost estimate)

Failure handling

API errors, refusals, empty output, invalid JSON, or schema-validation failures are written as status: "failed" with data: {}, so the scorer counts every labeled field as an error instead of silently dropping the document.