Triple

T8344585
Position Surface form Disambiguated ID Type / Status
Subject Petersen Events Center E196003 entity
Predicate locatedIn 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: [Petersen Events Center, locatedIn, Pittsburgh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pittsburgh
Context triple: [Petersen Events Center, locatedIn, 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. 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.
  • D. 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.
  • E. 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.
  • 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_69ca82edd63c8190b876b8465464c5fa completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fed6b588190ba5593859c8effc2 completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce1ce5a0c881909ee517678cdc4ef2 completed April 2, 2026, 7:38 a.m.
Created at: March 30, 2026, 5:58 p.m.