skills/semantic-seo-evidence/references/indexes/correction-index.json

[
  {
    "correction_id": "COR-RV2-001",
    "heading": "What is Semantic SEO?",
    "revision_status": "UPDATED",
    "target_term_ids": [
      "TERM-001"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-002",
    "heading": "What is an entity?",
    "revision_status": "UPDATED",
    "target_term_ids": [
      "TERM-002"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-003",
    "heading": "What is a Triple?",
    "revision_status": "REWRITTEN",
    "target_term_ids": [
      "TERM-003A",
      "TERM-003B"
    ],
    "runtime_action": "block_or_bound"
  },
  {
    "correction_id": "COR-RV2-004",
    "heading": "What is Topical Authority?",
    "revision_status": "REWRITTEN",
    "target_term_ids": [
      "TERM-004"
    ],
    "runtime_action": "block_or_bound"
  },
  {
    "correction_id": "COR-RV2-005",
    "heading": "What is a Query Network?",
    "revision_status": "UPDATED - FRAMEWORK TERM",
    "target_term_ids": [
      "TERM-005"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-006",
    "heading": "What is a Semantic Content Network?",
    "revision_status": "UPDATED - FRAMEWORK TERM",
    "target_term_ids": [
      "TERM-006"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-007",
    "heading": "What is Microsemantics?",
    "revision_status": "UPDATED - FRAMEWORK TERM",
    "target_term_ids": [
      "TERM-007"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-008",
    "heading": "What is Macrosemantics?",
    "revision_status": "UPDATED - FRAMEWORK TERM",
    "target_term_ids": [
      "TERM-008"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-009",
    "heading": "What is Topical Coverage?",
    "revision_status": "UPDATED - FRAMEWORK / AUDIT MODEL",
    "target_term_ids": [
      "TERM-009"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-010",
    "heading": "What is Historical Data for SEO?",
    "revision_status": "REWRITTEN",
    "target_term_ids": [
      "TERM-010"
    ],
    "runtime_action": "block_or_bound"
  },
  {
    "correction_id": "COR-RV2-011",
    "heading": "What is Relevance for Information Retrieval?",
    "revision_status": "REWRITTEN",
    "target_term_ids": [
      "TERM-011A"
    ],
    "runtime_action": "block_or_bound"
  },
  {
    "correction_id": "COR-RV2-012",
    "heading": "What are Representative and Represented Queries?",
    "revision_status": "REWRITTEN",
    "target_term_ids": [
      "TERM-012A",
      "TERM-012B"
    ],
    "runtime_action": "block_or_bound"
  },
  {
    "correction_id": "COR-RV2-013",
    "heading": "What is Semantic Distance?",
    "revision_status": "UPDATED",
    "target_term_ids": [
      "TERM-013"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-014",
    "heading": "What is Semantic Similarity?",
    "revision_status": "UPDATED",
    "target_term_ids": [
      "TERM-014A"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-015",
    "heading": "What is Semantic Relevance?",
    "revision_status": "UPDATED",
    "target_term_ids": [
      "TERM-015"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-016",
    "heading": "What is Natural Language Processing?",
    "revision_status": "UPDATED",
    "target_term_ids": [
      "TERM-016A"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-017",
    "heading": "What is Sliding Window in NLP?",
    "revision_status": "BACKGROUND",
    "target_term_ids": [
      "TERM-017A"
    ],
    "runtime_action": "block_or_bound"
  },
  {
    "correction_id": "COR-RV2-018",
    "heading": "What is Sequence Modeling in NLP?",
    "revision_status": "BACKGROUND - UPDATED",
    "target_term_ids": [
      "TERM-018"
    ],
    "runtime_action": "block_or_bound"
  },
  {
    "correction_id": "COR-RV2-019",
    "heading": "What is a Central Entity?",
    "revision_status": "UPDATED - FRAMEWORK TERM",
    "target_term_ids": [
      "TERM-019"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-020",
    "heading": "What is Source Context?",
    "revision_status": "UPDATED - FRAMEWORK TERM",
    "target_term_ids": [
      "TERM-020"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-021",
    "heading": "What is Central Search Intent?",
    "revision_status": "UPDATED - FRAMEWORK TERM",
    "target_term_ids": [
      "TERM-021"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-022",
    "heading": "What is a Knowledge Domain?",
    "revision_status": "REWRITTEN",
    "target_term_ids": [
      "TERM-022"
    ],
    "runtime_action": "block_or_bound"
  },
  {
    "correction_id": "COR-RV2-023",
    "heading": "What is a Contextual Domain?",
    "revision_status": "UPDATED - FRAMEWORK TERM",
    "target_term_ids": [
      "TERM-023"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-024",
    "heading": "What is a Contextual Layer?",
    "revision_status": "UPDATED - FRAMEWORK TERM",
    "target_term_ids": [
      "TERM-024"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-025",
    "heading": "What is Query Fan-out?",
    "revision_status": "ADDED",
    "target_term_ids": [
      "QRY-015"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-026",
    "heading": "What is Answer Span Extraction?",
    "revision_status": "ADDED - PATENT-DESCRIBED MECHANISM",
    "target_term_ids": [
      "IR-017",
      "IR-018"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-027",
    "heading": "What is a Generative Summary or AI Overview?",
    "revision_status": "ADDED",
    "target_term_ids": [
      "AIS-012"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-028",
    "heading": "What is Thematic Search or Result Clustering?",
    "revision_status": "ADDED - PATENT-DESCRIBED MECHANISM",
    "target_term_ids": [
      "TERM-005A",
      "TERM-011E",
      "TERM-011F"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-029",
    "heading": "What is Stateful or Conversational Search?",
    "revision_status": "ADDED",
    "target_term_ids": [
      "QRY-017"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-030",
    "heading": "What is Information Gain?",
    "revision_status": "ADDED - PATENT CONCEPT AND PRACTICAL QUALITY QUESTION",
    "target_term_ids": [
      "TERM-009"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-031",
    "heading": "What is Embedding-based Retrieval?",
    "revision_status": "ADDED",
    "target_term_ids": [
      "TERM-011C",
      "TERM-016C",
      "IR-016"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-032",
    "heading": "What is Hybrid Retrieval?",
    "revision_status": "ADDED",
    "target_term_ids": [
      "TERM-011D"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-033",
    "heading": "What is Retrieval-Augmented Generation (RAG)?",
    "revision_status": "ADDED",
    "target_term_ids": [
      "AIS-010"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-034",
    "heading": "What is Grounding?",
    "revision_status": "ADDED",
    "target_term_ids": [
      "AIS-011"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-035",
    "heading": "What are Citation and Attribution in AI Search?",
    "revision_status": "ADDED",
    "target_term_ids": [
      "AIS-014",
      "AIS-015"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-036",
    "heading": "What is Source Eligibility?",
    "revision_status": "ADDED - PRACTICAL TERM",
    "target_term_ids": [
      "AIS-013"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-037",
    "heading": "What is Agentic or Reasoning Search?",
    "revision_status": "ADDED",
    "target_term_ids": [
      "AIS-012",
      "AIS-016"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-038",
    "heading": "What are GEO and AEO?",
    "revision_status": "ADDED - INDUSTRY TERMS",
    "target_term_ids": [
      "AIS-021",
      "AIS-022"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "correction_id": "COR-RV2-039",
    "heading": "What is AI Visibility?",
    "revision_status": "ADDED",
    "target_term_ids": [
      "AIS-023"
    ],
    "runtime_action": "retain_with_boundary"
  },
  {
    "retired_claim_id": "RET-RV2-001",
    "original_claim": "US12265560 describes an LLM writing subqueries",
    "decision_type": "retire",
    "runtime_action": "block"
  },
  {
    "retired_claim_id": "RET-RV2-002",
    "original_claim": "A clean triple is precisely the shape a generative engine extracts",
    "decision_type": "narrow",
    "runtime_action": "replace_with_boundary"
  },
  {
    "retired_claim_id": "RET-RV2-003",
    "original_claim": "Information Gain is a granted universal ranking signal",
    "decision_type": "narrow",
    "runtime_action": "replace_with_boundary"
  },
  {
    "retired_claim_id": "RET-RV2-004",
    "original_claim": "The Blind Librarian chapter is closed",
    "decision_type": "retire",
    "runtime_action": "block"
  },
  {
    "retired_claim_id": "RET-RV2-005",
    "original_claim": "Citation assignment is exactly embedding similarity",
    "decision_type": "retire",
    "runtime_action": "block"
  },
  {
    "retired_claim_id": "RET-RV2-006",
    "original_claim": "Header-defined passages are the unit and heading-query match is scored",
    "decision_type": "narrow",
    "runtime_action": "replace_with_boundary"
  },
  {
    "retired_claim_id": "RET-RV2-007",
    "original_claim": "NLP is superseded",
    "decision_type": "retire",
    "runtime_action": "block"
  },
  {
    "retired_claim_id": "RET-RV2-008",
    "original_claim": "Every important passage must be completely self-sufficient",
    "decision_type": "narrow",
    "runtime_action": "replace_with_boundary"
  },
  {
    "retired_claim_id": "RET-RV2-009",
    "original_claim": "RNN/LSTM are history",
    "decision_type": "retire",
    "runtime_action": "block"
  },
  {
    "retired_claim_id": "RET-RV2-010",
    "original_claim": "Knowledge Domain stands unchanged",
    "decision_type": "retire",
    "runtime_action": "block"
  },
  {
    "retired_claim_id": "RET-RV2-011",
    "original_claim": "Contextual layers are executable fan-out queries",
    "decision_type": "narrow",
    "runtime_action": "replace_with_boundary"
  },
  {
    "retired_claim_id": "RET-RV2-012",
    "original_claim": "Reasoning engines verify every claim and abstain when confidence is low",
    "decision_type": "narrow",
    "runtime_action": "replace_with_boundary"
  }
]