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Metehan Entity Extractor Workflow

runnable

Describes the use of the Metehan Entity Extractor tool for preliminary entity extraction.

semanticsentity-seoentity-extractiontools
Agent trigger phrases: extract entities quickly · use Metehan tool · entity triage list · Metehan for entity-seo · get entity salience · Metehan tool workflow · baseline entity extraction · optimize entity pipeline

Metehan Entity Extractor (quick-start extraction):

Metehan's free Entity Extractor at metehan.ai/tools/entity-extractor provides rapid entity recognition from a URL or raw text block. It's the fastest way to get a baseline entity list before running the full entity-seo pipeline.

What it extracts:

  • Named entities — People, Organizations, Places, Products
  • Concepts — Abstract topics and themes
  • Keywords — High-frequency salient terms
  • Per entity: salience score (0–1), type, and (where available) Wikipedia/Wikidata link

Workflow — entity baseline:

  1. Input — paste a URL (competitor top-ranker) OR raw text (your draft).
  2. Extract — click Run. Results appear as a ranked list.
  3. Export — copy the list or download CSV.
  4. Triage — bucket entities into three groups:
    • Must have — salience ≥ 0.6, directly on-topic. These are non-negotiable for your content.
    • Should have — salience 0.3–0.59, supporting entities. Include in H2/H3 subsections.
    • Could have — salience < 0.3, context entities. Use sparingly in body copy.
  5. Feed into entity-seo — use the Must + Should list as the entity checklist for the main entity-seo workflow.
  6. Verify with wikidata-entity-lookup — any entity without a Wikipedia/Wikidata link from the Metehan tool should be checked manually; the Metehan tool misses some less-common entities that do exist in Wikidata.

Competitor delta workflow:

Run the Entity Extractor on your page AND the top 3 competitors for the same query:

  1. Extract entities from your page → list A
  2. Extract entities from competitor 1 → list B
  3. Extract entities from competitor 2 → list C
  4. Extract entities from competitor 3 → list D
  5. Find entities in (B ∩ C ∩ D) but NOT in A → critical gap list
  6. Find entities in (B ∪ C ∪ D) but NOT in A with salience ≥ 0.4 → opportunity list

Add critical gap entities to your next rewrite. Opportunity entities become H3 candidates.

Accuracy vs Google NLP API:

The Metehan tool is adequate for triage but less accurate than Google Cloud Natural Language API for edge cases (non-English, emerging tech terms, regional brands). For publish-gate decisions, re-run through Google NLP API. For routine content planning, the Metehan tool is sufficient.