Triple

T179605
Position Surface form Disambiguated ID Type / Status
Subject Oslo E3654 entity
Predicate locatedIn P40 FINISHED
Object Oslo County E22828 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: Oslo County | Statement: [Oslo, locatedIn, Oslo County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oslo County
Context triple: [Oslo, locatedIn, Oslo County]
  • A. Oslo County chosen
    Oslo County is the administrative region that encompasses Norway’s capital city, Oslo, serving as a central hub for the country’s political, cultural, and academic institutions.
  • B. Douglas County
    Douglas County is a county in western Nevada known for encompassing part of the Lake Tahoe region and serving as a key residential and recreational area near Carson City and the California border.
  • C. Washington County
    Washington County is a county in southwestern Pennsylvania that forms part of the greater Pittsburgh metropolitan area.
  • D. Washington County
    Washington County was a former administrative subdivision of the District of Columbia that encompassed the area outside the cities of Washington and Georgetown on the Maryland side of the Potomac River.
  • E. King County
    King County is a populous county in the U.S. state of Washington that includes Seattle as its largest city and economic center.
  • 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_69a25374990081909766d30c79a18e0e completed Feb. 28, 2026, 2:31 a.m.
NER Named-entity recognition batch_69a25900709c8190a65e778936be5dd5 completed Feb. 28, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3441a5fb08190971136c2ec6e79ee completed Feb. 28, 2026, 7:38 p.m.
Created at: Feb. 28, 2026, 2:39 a.m.