Triple

T16626553
Position Surface form Disambiguated ID Type / Status
Subject The High Life E403960 entity
Predicate settingLocation P40 FINISHED
Object Pittsburgh E19280 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: Pittsburgh | Statement: [The High Life, settingLocation, Pittsburgh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pittsburgh
Context triple: [The High Life, settingLocation, Pittsburgh]
  • A. Pittsburg
    Pittsburg is an industrial and residential city in Contra Costa County in the San Francisco Bay Area of California.
  • B. Pittsburgh, Pennsylvania chosen
    Pittsburgh, Pennsylvania is a major U.S. city in western Pennsylvania known for its historic steel industry, numerous bridges, and strong educational and technology sectors.
  • C. PGH
    PGH is the Philippine General Hospital, a major government-owned tertiary referral and teaching hospital in Manila affiliated with the University of the Philippines.
  • D. Duquesne, Pennsylvania
    Duquesne, Pennsylvania is a small industrial city along the Monongahela River near Pittsburgh, historically known as a major steel-producing community in the American Rust Belt.
  • E. Oakland, Pittsburgh
    Oakland is a major Pittsburgh neighborhood known as the city’s academic and medical hub, home to institutions like the University of Pittsburgh and Carnegie Mellon University.
  • 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_69d883897eb481909eaaa088ba9918d9 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e375530ed081908337dc5c6360d733 completed April 18, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a2b3a608190ad8d2b653cd8785d completed May 10, 2026, 1:37 p.m.
Created at: April 10, 2026, 5:17 a.m.