{"observation":{"id":"38fc2de5-4406-486b-9a50-fa39c4b5e88a","tool":"retab","tool_name":"Retab","criterion":"schema-adherence","criterion_name":"Schema Adherence","criterion_definition":"Does the output follow the supplied JSON schema hierarchy exactly, with correct nesting, field names, and data types?","criterion_evidence_type":"transformation","criterion_rank_role":"decisive","criterion_rank_role_reason":"If the output does not match the requested JSON schema exactly, the extracted data cannot be reliably consumed or queried, so this is core to the task. (3 of 3 judges)","scenario":"invoice-pdf","scenario_name":"Invoice PDF","group_tag":"financial-document-extraction","scenario_description":"A 2-page broadcast advertising invoice PDF with 8 line items, complex time/day fields, large dollar amounts, and compliance text, used to test hierarchical line-item extraction and financial validation.","modality":"pdf","input_text":null,"input_artifact_refs":[{"alt":null,"url":null,"role":null,"filename":"Invoice PDF.pdf"}],"stresses":["Nested line-item hierarchy extraction","Multi-page line-item continuity across a page break","Large dollar amount precision and total validation","Parsing time slots, day patterns, and air dates","Extraction of alphanumeric ad IDs and reference codes","Structured metadata mapping for advertiser, station, billing, and remit sections","Political advertising and FCC compliance text recognition"],"verdict":"worked","score":null,"score_total":null,"note":"Builds the requested invoice hierarchy with separate invoice_metadata, advertiser, station, account_details, billing_address, remit_address, flight_dates, line_items, and summary objects instead of a flat OCR dump.","evidence_state":"verified","source":null,"artifacts":[{"url":"https://d3epheqghktydj.cloudfront.net/research-media-retab-extracted-invoice-metadata-2b6610b8f928.png","role":"output","alt":null},{"url":"https://d3epheqghktydj.cloudfront.net/research-media-retab-invoice-schema-order-4df9e06bef88.png","role":"input","alt":null},{"url":"https://d3epheqghktydj.cloudfront.net/research-media-retab-invoice-output-f9a8e57e98e8.json","role":"output","alt":null}],"run_id":"ec4d736d-95f9-4c88-884c-e280435f7b7b","study_title":"Extract and query structured data from documents using natural language","study_kind":"generation","research_task":"86b9y25e5","tested_at":null,"completeness":"input-and-output","input":{"state":"not-captured","text":null,"files":[],"modality":"pdf","stresses":["Nested line-item hierarchy extraction","Multi-page line-item continuity across a page break","Large dollar amount precision and total validation","Parsing time slots, day patterns, and air dates","Extraction of alphanumeric ad IDs and reference codes","Structured metadata mapping for advertiser, station, billing, and remit sections","Political advertising and FCC compliance text recognition"]},"tool_page_slug":"retab","tool_url":"https://aidemos.com/tools/retab","permalink":"https://aidemos.com/evidence/38fc2de5-4406-486b-9a50-fa39c4b5e88a","api_url":"https://ai.aidemos.com/v1/observations/38fc2de5-4406-486b-9a50-fa39c4b5e88a"},"peers":[{"id":"c01474f8-d601-4535-b19c-9ab5759d7f35","tool":"datalab","tool_name":"Datalab","verdict":"worked","score":null,"score_total":null,"note":"Reconstructs the invoice into nested JSON objects and arrays that follow the supplied schema, including invoice_metadata and line_items rather than returning generic OCR text.","artifact_count":5,"thumbnail":"https://d3epheqghktydj.cloudfront.net/research-media-datalab-invoice-metadat-1c39e0c1c45e.png","evidence_url":"https://aidemos.com/evidence/c01474f8-d601-4535-b19c-9ab5759d7f35"},{"id":"ad656fd6-a7c6-4174-a1a5-71f32b26d964","tool":"extend-ai","tool_name":"Extend AI","verdict":"worked","score":null,"score_total":null,"note":"The invoice output is reconstructed as nested JSON sections — invoice_metadata, advertiser, station, addresses, flight_dates, line_items, and summary — instead of raw OCR.","artifact_count":2,"thumbnail":"https://d3epheqghktydj.cloudfront.net/research-media-extendai-invoice-output-9eaac6626f6c.json","evidence_url":"https://aidemos.com/evidence/ad656fd6-a7c6-4174-a1a5-71f32b26d964"},{"id":"e21e3065-67a9-44b0-a7d5-4534cc545780","tool":"landing-ai","tool_name":"Landing AI","verdict":"worked","score":null,"score_total":null,"note":"Reconstructs the requested invoice hierarchy in structured JSON, filling invoice_metadata, advertiser, station, line_items, and summary objects instead of returning a flat extraction.","artifact_count":4,"thumbnail":"https://d3epheqghktydj.cloudfront.net/research-media-landing-ai-extracted-invoice-metadata-57a291c39e3d.png","evidence_url":"https://aidemos.com/evidence/e21e3065-67a9-44b0-a7d5-4534cc545780"},{"id":"0b3ba3e3-dd88-4377-97f7-2da41c08c915","tool":"llamaparse","tool_name":"LlamaParse","verdict":"worked","score":null,"score_total":null,"note":"Keeps the invoice hierarchy intact, emitting invoice_metadata, advertiser, station, line_items, and summary objects rather than flat OCR text.","artifact_count":2,"thumbnail":"https://d3epheqghktydj.cloudfront.net/research-media-llamaparse-invoice-metadata-af804b493598.png","evidence_url":"https://aidemos.com/evidence/0b3ba3e3-dd88-4377-97f7-2da41c08c915"},{"id":"d1acf6ae-95ec-460a-bac2-aed663d491c5","tool":"nanonets","tool_name":"Nanonets","verdict":"worked","score":null,"score_total":null,"note":"It preserves the invoice hierarchy exactly as requested, filling dedicated objects for invoice_metadata, advertiser, station, account_details, billing_address, remit_address, flight_dates, line_items, and summary.","artifact_count":2,"thumbnail":"https://d3epheqghktydj.cloudfront.net/research-media-docstrange-nanonets-invoice-output-9dc0f476da4c.json","evidence_url":"https://aidemos.com/evidence/d1acf6ae-95ec-460a-bac2-aed663d491c5"},{"id":"3d48880c-53de-43f1-b4b6-4da534758c2b","tool":"reducto","tool_name":"Reducto","verdict":"worked","score":null,"score_total":null,"note":"Reconstructs the invoice into the requested nested JSON hierarchy, populating invoice_metadata, advertiser, station, account_details, billing_address, remit_address, flight_dates, line_items, and summary sections.","artifact_count":3,"thumbnail":"https://d3epheqghktydj.cloudfront.net/research-media-reducto-invoice-metadata-c12acb4fc069.png","evidence_url":"https://aidemos.com/evidence/3d48880c-53de-43f1-b4b6-4da534758c2b"},{"id":"15ef12f7-5460-42d4-99d5-9ee4785c8552","tool":"unstract","tool_name":"Unstract","verdict":"worked","score":null,"score_total":null,"note":"Populates the requested invoice hierarchy into dedicated sections for invoice_metadata, advertiser, station, account_details, billing_address, remit_address, flight_dates, line_items, and summary.","artifact_count":2,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/18ce6c9c9f314db694ae8439172b4041.png?v=1","evidence_url":"https://aidemos.com/evidence/15ef12f7-5460-42d4-99d5-9ee4785c8552"}],"other_criteria":[{"id":"a764ebf7-c927-4d60-92f5-68838d5361f4","criterion":"extraction-accuracy","criterion_name":"Extraction Accuracy","rank_role":"decisive","verdict":"mixed","score":null,"score_total":null,"note":"Retains the source label in payment_terms, returning Payment Terms 30 Days instead of only the requested value, so a cleanup step is needed.","artifact_count":1,"evidence_url":"https://aidemos.com/evidence/a764ebf7-c927-4d60-92f5-68838d5361f4"},{"id":"545de688-ed6b-41cf-aa4b-3f3edbf02217","criterion":"extraction-accuracy","criterion_name":"Extraction Accuracy","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Extracts key invoice metadata values as typed fields, including invoice_number 4064621-1, invoice_date 2012-10-28, estimate_number 2968, and order_number 4064621.","artifact_count":1,"evidence_url":"https://aidemos.com/evidence/545de688-ed6b-41cf-aa4b-3f3edbf02217"},{"id":"9e5c5bc7-673d-467a-90cc-75c7c06dea40","criterion":"extraction-accuracy","criterion_name":"Extraction Accuracy","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Carries the financial summary through consistently, including agency_commission 4462.5, aired_spots 8, gross_total 29750, and net_amount_due 25287.5.","artifact_count":1,"evidence_url":"https://aidemos.com/evidence/9e5c5bc7-673d-467a-90cc-75c7c06dea40"},{"id":"0768d86c-2233-428d-9d43-a4c32b86f2c2","criterion":"semantic-field-enrichment","criterion_name":"Semantic Field Enrichment","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Derives scheduling fields beyond raw OCR, including day_of_week Su and days_pattern ------S for a line item, along with air_time, time_slot, and ad_id.","artifact_count":1,"evidence_url":"https://aidemos.com/evidence/0768d86c-2233-428d-9d43-a4c32b86f2c2"},{"id":"b78d37af-33a7-4f25-91f5-6a7c39e2f334","criterion":"structural-clean-output","criterion_name":"Structural Clean Output","rank_role":"context","verdict":"mixed","score":null,"score_total":null,"note":"Does not preserve the schema-defined property order, so consumers that rely on key order need an extra formatting pass.","artifact_count":2,"evidence_url":"https://aidemos.com/evidence/b78d37af-33a7-4f25-91f5-6a7c39e2f334"},{"id":"351eae64-d136-45cf-bf96-05708a002c49","criterion":"table-and-record-completeness","criterion_name":"Table & Record Completeness","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Reconstructs all 8 advertising line items as separate records without duplication or omission.","artifact_count":1,"evidence_url":"https://aidemos.com/evidence/351eae64-d136-45cf-bf96-05708a002c49"}],"appears_in":[{"page_type":"ranking","slug":"document-extraction","title":"Best AI Tools for Extracting Structured Data from PDFs and Business Documents","url":"https://aidemos.com/best/document-extraction","binding":"run"},{"page_type":"tool","slug":"unstract","title":null,"url":"https://aidemos.com/tools/unstract","binding":"run"}],"same_scenario":[{"id":"c01474f8-d601-4535-b19c-9ab5759d7f35","tool":"datalab","tool_name":"Datalab","verdict":"worked","score":null,"score_total":null,"note":"Reconstructs the invoice into nested JSON objects and arrays that follow the supplied schema, including invoice_metadata and line_items rather than returning generic OCR text."},{"id":"ad656fd6-a7c6-4174-a1a5-71f32b26d964","tool":"extend-ai","tool_name":"Extend AI","verdict":"worked","score":null,"score_total":null,"note":"The invoice output is reconstructed as nested JSON sections — invoice_metadata, advertiser, station, addresses, flight_dates, line_items, and summary — instead of raw OCR."},{"id":"e21e3065-67a9-44b0-a7d5-4534cc545780","tool":"landing-ai","tool_name":"Landing AI","verdict":"worked","score":null,"score_total":null,"note":"Reconstructs the requested invoice hierarchy in structured JSON, filling invoice_metadata, advertiser, station, line_items, and summary objects instead of returning a flat extraction."},{"id":"0b3ba3e3-dd88-4377-97f7-2da41c08c915","tool":"llamaparse","tool_name":"LlamaParse","verdict":"worked","score":null,"score_total":null,"note":"Keeps the invoice hierarchy intact, emitting invoice_metadata, advertiser, station, line_items, and summary objects rather than flat OCR text."},{"id":"d1acf6ae-95ec-460a-bac2-aed663d491c5","tool":"nanonets","tool_name":"Nanonets","verdict":"worked","score":null,"score_total":null,"note":"It preserves the invoice hierarchy exactly as requested, filling dedicated objects for invoice_metadata, advertiser, station, account_details, billing_address, remit_address, flight_dates, line_items, and summary."},{"id":"3d48880c-53de-43f1-b4b6-4da534758c2b","tool":"reducto","tool_name":"Reducto","verdict":"worked","score":null,"score_total":null,"note":"Reconstructs the invoice into the requested nested JSON hierarchy, populating invoice_metadata, advertiser, station, account_details, billing_address, remit_address, flight_dates, line_items, and summary sections."},{"id":"15ef12f7-5460-42d4-99d5-9ee4785c8552","tool":"unstract","tool_name":"Unstract","verdict":"worked","score":null,"score_total":null,"note":"Populates the requested invoice hierarchy into dedicated sections for invoice_metadata, advertiser, station, account_details, billing_address, remit_address, flight_dates, line_items, and summary."}]}