Triple

T16943785
Position Surface form Disambiguated ID Type / Status
Subject Scappoose Public Library E411013 entity
Predicate serviceArea P82 FINISHED
Object Scappoose, Oregon E87505 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: Scappoose, Oregon | Statement: [Scappoose Public Library, serviceArea, Scappoose, Oregon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Scappoose, Oregon
Context triple: [Scappoose Public Library, serviceArea, Scappoose, Oregon]
  • A. Scappoose, Oregon chosen
    Scappoose, Oregon is a small city in northwestern Oregon known as a bedroom community of the Portland metropolitan area with a mix of rural and suburban character.
  • B. Scottsburg, Oregon
    Scottsburg, Oregon is a small unincorporated community in Douglas County situated along the Umpqua River in western Oregon.
  • C. Scio, Oregon
    Scio, Oregon is a small rural city in the Willamette Valley known for its historic covered bridges and agricultural community.
  • D. Nelscott, Oregon
    Nelscott, Oregon was a former coastal community that became part of present-day Lincoln City on the central Oregon coast.
  • E. Brownsville, Oregon
    Brownsville, Oregon is a small historic city in the Willamette Valley known for its 19th-century architecture and as a filming location for the movie "Stand by Me."
  • 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_69d886c886688190967be07322597ac9 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cfb08da88190b07c32652bbc1534 completed April 18, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012eccd1e48190aa0dc64562d6ff1f completed May 11, 2026, 1:20 a.m.
Created at: April 10, 2026, 5:31 a.m.