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It outlines detailed instructions and strict rules for extracting comprehensive metadata, including title, language, abstract, keywords, table of contents, and frequently asked questions. The document emphasizes language consistency across all metadata fields, prioritizes original document language, and provides specific guidelines for title generation, including feature detection and formatting to ensure clarity and conciseness within a 100-character limit. It also details requirements for abstract length, keyword selection, table of contents structure, and FAQ generation, ensuring diversity and relevance. The process aims to produce structured, SEO-friendly metadata for effective document organization and retrieval, with a clear fallback to 'General' category if no specific category matches confidently.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/document-metadata-extraction-multimodal/180724/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/document-metadata-extraction-multimodal/180724.png","ImageObject",300,407,{"name":92,"@type":93},"Oliver","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-09-02",true,{"@type":102,"interactionType":103,"userInteractionCount":44},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the main purpose of this document?","Question",{"text":112,"@type":113},"The main purpose of this document is to define the rules and guidelines for extracting metadata from documents that contain both text and images.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What are the key requirements for the output of the metadata extraction process?",{"text":117,"@type":113},"The output must be a single raw JSON object containing all specified fields (title, title_en, language, abstract, keywords, category, toc, faqs), with strict adherence to language consistency, character limits, and formatting rules.",{"name":119,"@type":110,"acceptedAnswer":120},"How is the document's language determined?",{"text":121,"@type":113},"The document's language is determined primarily by the dominant language in meaningful natural language sentences, considering body text, image text, and then the document title or file name as fallback signals.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},180724,1788341901,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":44,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":44,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":129,"read_time":143,"preview_page_count":4},8796095461610,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","| Dataset |  | Size (test set) | Shape | Nonempty Rate |\n| --- | --- | --- | --- | --- |\n| Name | Description |  |  |  |\n| MNIST [LeCun, 1998] | Handwriting digits | 10,000 | [28􀀂28] | 17.90% |\n| StanfordCars [Krause et al., 2013] | Car images | 8,041 | [360􀀂640]􀀃 | 98.73% |\n| CMUARCTIC [Kominek et al., 2003] | English speech | 1,132 | [64,321]􀀃 | 99.72% |\n\n| Model | Optimizer | Learning Rate | Topology and Function |\n| --- | --- | --- | --- |\n| CNN | SGD | 0.01 | conv: 1 ! 10 ! 20, kernel 5 􀀂 5; fc: 320 ! 50 ! 10 |\n| MLP | SGD | 0.01 | 784 ! 64 ! 10, ReLU, Softmax |\n\n|  |  |  |  |  |  |  |  |  FHE  |  |  |  | CHEM |  |  |  |\n| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |\n| 354.21 352.62 |  |  |  |  |  |  | 348.06 347.13 |  |  |  |  |  |  |  |  |\n|  |  |  |  |  |  |  |  |  | |  |  | |  |  |  |\n|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |\n|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |\n|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |\n|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |\n|  |  | 53.02 |  |  | 51.94 |  |  |  |  | 47.15 |  |  | 47.36 |  |  |\n|  |  | |  |  | |  |  |  |  | |  |  | |  |  |","cbCailB0B2VNrRyu","https://ap.wps.com/l/cbCailB0B2VNrRyu","pdf",348726,"English","# Document Metadata Extraction (Multimodal)\n## Instructions\n## Language Rules\n## Field Specifications\n### Title Rules\n### `title_en`\n### `language`\n### abstract\n### `keywords`\n### `toc`\n### `faqs`\n### `category`\n## Output Requirements (STRICT)\n## Inputs","[{\"question\":\"What is the main purpose of this document?\",\"answer\":\"The main purpose of this document is to define the rules and guidelines for extracting metadata from documents that contain both text and images.\"},{\"question\":\"What are the key requirements for the output of the metadata extraction process?\",\"answer\":\"The output must be a single raw JSON object containing all specified fields (title, title_en, language, abstract, keywords, category, toc, faqs), with strict adherence to language consistency, character limits, and formatting rules.\"},{\"question\":\"How is the document's language determined?\",\"answer\":\"The document's language is determined primarily by the dominant language in meaningful natural language sentences, considering body text, image text, and then the document title or file name as fallback signals.\"}]","Document Metadata Extraction (Multimodal) | PDF",23]