Triple

T744900
Position Surface form Disambiguated ID Type / Status
Subject Seattle metropolitan area E15319 entity
Predicate hasCounty P285 FINISHED
Object Jefferson County E44668 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: Jefferson County | Statement: [Seattle metropolitan area, hasCounty, Jefferson County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jefferson County
Context triple: [Seattle metropolitan area, hasCounty, Jefferson County]
  • A. Jefferson County chosen
    Jefferson County is a county on Washington State’s Olympic Peninsula, known for its rugged Pacific coastline, portions of Olympic National Park, and maritime communities such as Port Townsend.
  • B. Wayne County
    Wayne County is a populous county in southeastern Michigan that includes the city of Detroit and serves as a major industrial and cultural hub of the state.
  • C. Wayne County
    Wayne County is a county in southeastern Georgia known for its rural communities, forestry, and transportation routes connecting coastal and inland parts of the state.
  • D. Madison County
    Madison County is a county in central Mississippi, located in the Jackson metropolitan area and known for its rapidly growing suburban communities.
  • E. Lawrence County
    Lawrence County is a county in western Pennsylvania that forms part of the greater Pittsburgh metropolitan region.
  • 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_69a49358aa308190adbc9b5a0a2adcf9 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a61217b881908592096b1edacb8a completed March 1, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac16f360208190affd6282a1040d9a completed March 7, 2026, 12:15 p.m.
Created at: March 1, 2026, 7:37 p.m.