Triple

T2511449
Position Surface form Disambiguated ID Type / Status
Subject Snohomish County E52708 entity
Predicate hasCountySeat P383 FINISHED
Object Everett E136257 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: Everett | Statement: [Snohomish County, hasCountySeat, Everett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Everett
Context triple: [Snohomish County, hasCountySeat, Everett]
  • A. Everett
    Everett is a city in Middlesex County, Massachusetts, located just north of Boston and known for its industrial history and urban residential character.
  • B. Everett chosen
    Everett is a city in western Washington State, known as a major industrial and maritime hub north of Seattle and home to a large Boeing aircraft assembly plant.
  • C. Everett
    Everett is a surname of English origin borne by various notable individuals, including American politician and orator Edward Everett.
  • D. Bremerton
    Bremerton is a waterfront city in Washington State known for its naval shipyard and ferry connection to Seattle across Puget Sound.
  • E. Berkley
    Berkley is a small rural town in Bristol County, Massachusetts, known for its quiet residential character and proximity to the Taunton River.
  • 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_69ab4958e76481908a235377dd921c9e completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd1eeaaac8190a6652861dd42e6b9 completed March 7, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1fac64a881909ed527a7c50ba720 completed March 9, 2026, 7:29 p.m.
Created at: March 6, 2026, 9:46 p.m.