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Extract structured data and entities from existing HTML, Markdown, or text files to audit metadata availability.
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SOC 職業分類に基づく
Normalize named entities and concept variants into canonical forms using controlled vocabularies or standard taxonomies.
Analyze vocabulary overlap and identify named entities unique to domain/document corpora.
Transform lengthy documents into a semantic tree structure. It extracts sections, summaries, and hierarchies optimized for use with Large Language Models (LLMs).
Design formal ontologies using OWL/RDFS. Defines classes, properties, and relationships for complex semantic modeling.
Systematic cataloging of information assets. Creates comprehensive inventories or card sorting materials from content.
Generate JSON-LD structured data for web content. Maps content to Schema.org types to improve search engine understanding and rich result eligibility.
| name | semantic-extract |
| description | Extract structured data and entities from existing HTML, Markdown, or text files to audit metadata availability. |
| required_roles | {"scribe":"roles/scribe.editor"} |
| personas | ["content-strategist","data-analyst"] |
Parse documents to identify and extract existing structured data (tables, lists, headers) and potential entities, converting them into a raw structured format for audit or migration.
PATH - The source document to process.OUTPUT_FORMAT - (Optional) "json", "csv", "yaml" (default: "json").PATH.OUTPUT_FORMAT.A structured object containing the extracted data, keyed by the source element (e.g., "Table 1", "Frontmatter").