Triple

T1781557
Position Surface form Disambiguated ID Type / Status
Subject Carnegie of Pittarrow E39300 entity
Predicate familyName P18 FINISHED
Object Carnegie E229 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: Carnegie | Statement: [Carnegie of Pittarrow, familyName, Carnegie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carnegie
Context triple: [Carnegie of Pittarrow, familyName, Carnegie]
  • A. Carnegie chosen
    Carnegie is a Scottish surname most famously associated with industrialist and philanthropist Andrew Carnegie.
  • B. Carnegie, Pennsylvania
    Carnegie, Pennsylvania is a small borough in Allegheny County near Pittsburgh, historically tied to the region’s steel industry and local immigrant communities.
  • C. Peabody
    Peabody is a suburban city in northeastern Massachusetts known for its location on the North Shore and its historical ties to the leather industry.
  • D. Bessemer
    Bessemer is a surname most notably associated with Sir Henry Bessemer, the English inventor who revolutionized steel production in the 19th century.
  • E. Bessemer
    Bessemer is an industrial city in Jefferson County, Alabama, historically known for its steelmaking and manufacturing.
  • 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_69a88630519c8190a17addd83c4a3ef4 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64e22d6881909ba6ec120b320918 completed March 6, 2026, 5:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69adc9a4ee9c8190a6cdb5df16a48711 completed March 8, 2026, 7:10 p.m.
Created at: March 4, 2026, 7:31 p.m.