Datasets:
Tasks:
Document Question Answering
Size:
n<1K
Tags:
benchmark
document-ai
information-extraction
structured-extraction
key-information-extraction
ocr
License:
| from scorer import score_standardization | |
| def test_array_matching_is_order_independent(): | |
| schema = { | |
| "type": "object", | |
| "properties": { | |
| "items": { | |
| "type": "array", | |
| "items": { | |
| "type": "object", | |
| "properties": { | |
| "sku": {"type": "string"}, | |
| "qty": {"type": "number"}, | |
| }, | |
| }, | |
| } | |
| }, | |
| } | |
| label = {"items": [{"sku": "A-1", "qty": 2}, {"sku": "B-2", "qty": 3}]} | |
| result = {"items": [{"sku": "B 2", "qty": 3.0}, {"sku": "a1", "qty": 2}]} | |
| assert score_standardization(result=result, schema=schema, label=label)["final"] == 1.0 | |
| def test_both_blank_non_array_fields_are_skipped(): | |
| schema = { | |
| "type": "object", | |
| "properties": { | |
| "empty": {"type": "string"}, | |
| "name": {"type": "string"}, | |
| }, | |
| } | |
| label = {"empty": "", "name": "Acme, Inc."} | |
| result = {"empty": "", "name": "ACME INC"} | |
| out = score_standardization(result=result, schema=schema, label=label) | |
| assert out["non_array"]["total"] == 1 | |
| assert out["final"] == 1.0 | |
| def test_extra_array_item_field_reduces_similarity(): | |
| schema = { | |
| "type": "object", | |
| "properties": { | |
| "items": { | |
| "type": "array", | |
| "items": { | |
| "type": "object", | |
| "properties": { | |
| "sku": {"type": "string"}, | |
| }, | |
| }, | |
| } | |
| }, | |
| } | |
| label = {"items": [{"sku": "A"}]} | |
| result = {"items": [{"sku": "A", "extra": "not requested"}]} | |
| assert score_standardization(result=result, schema=schema, label=label)["final"] == 0.5 | |