Graph Search

​

Notes

• Authenticated, no credits — send the same X-API-Key header as every Tako endpoint. Graph calls consume no credits; rate limits are 180/minute and 10,000/day.
• Use graph search to discover and confirm what data exists before you query it. Resolve the metric and the entity you care about here, then ask Search (/v3/search) or Answer (/v1/answer) for that specific entity + metric combination — and pin the resolved ids via sources.data.node_ids.
• Each result is a GraphNode whose id you can pass straight to Graph Related to explore what it connects to.

​

Scoping with types

• metric — a measure (e.g. “GDP”, “stock price”).
• entity — a thing the metric is tracked for (e.g. a country, a company).

​

Steering the ranking with label

# The airline, not the country
curl "https://tako.com/api/beta/graph/search?q=air%20china&label=ORG" \
  -H "X-API-Key: $TAKO_API_KEY"

• Values: PERSON, ORG, GPE, LOC, PRODUCT, EVENT, LANGUAGE, MONEY, METRIC, STOCK_TICKER, WEBSITE. Sports teams are ORG. An unknown value is a 400.
• Auto-inference is on by default (infer_label=true): with no explicit label, Tako detects the entities in q and applies the matching boost. The labels it found come back in inferred_labels — an empty list means inference ran and found nothing; the key is absent when inference didn’t run. Disable with infer_label=false (also 0/no/off); passing an explicit label also disables inference.
• Each node reports its own label and subtype (e.g. Countries, Companies) in the response — read them to pick the right node rather than assuming the list is filtered.

​

Example response

{
  "results": [
    {
      "id": "ent::air_china_limited::6af29d2b",
      "type": "entity",
      "name": "Air China Limited",
      "aliases": ["Air China", "Air China Ltd.", "CCA"],
      "description": "Air China Limited, together with its subsidiaries, provides air passenger, air cargo, and airline-related services…",
      "subtype": "Companies",
      "label": "ORG"
    }
  ]
}