Triple

T7269701
Position Surface form Disambiguated ID Type / Status
Subject Prince of Wales Island E161068 entity
Predicate governingBody P46 FINISHED
Object City of Hydaburg E381394 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: City of Hydaburg | Statement: [Prince of Wales Island, governingBody, City of Hydaburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Hydaburg
Context triple: [Prince of Wales Island, governingBody, City of Hydaburg]
  • A. Hydaburg chosen
    Hydaburg is a small city on Prince of Wales Island in Alaska known as a central community for the Haida people and their culture.
  • B. City of Nome
    The City of Nome is the municipal government responsible for administering and providing local services to the remote, historically gold-rush-era city of Nome in western Alaska.
  • C. Petersburg, Alaska
    Petersburg, Alaska is a small fishing town in Southeast Alaska known for its strong Norwegian heritage and thriving commercial fishing industry.
  • D. City of Elmendorf
    The City of Elmendorf is a small municipality located in Bexar County, Texas, within the San Antonio metropolitan area.
  • E. Sitka
    Sitka is a historic coastal city in southeastern Alaska known for its Tlingit and Russian heritage, scenic island setting, and abundant wildlife.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c6885181008190b419040e22939c7c completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eae9f8bc8190a8c31cc29926919c completed March 27, 2026, 8:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c810bb0d808190b6ade5592fce2c15 completed March 28, 2026, 5:32 p.m.
Created at: March 27, 2026, 2:58 p.m.