Triple

T22007686
Position Surface form Disambiguated ID Type / Status
Subject Pittsburgh Rens E543492 entity
Predicate homeCity P263 FINISHED
Object Pittsburgh NE NERFINISHED

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: [Pittsburgh Rens, homeCity, Pittsburgh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pittsburgh
Context triple: [Pittsburgh Rens, homeCity, 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 IATA airport code for Pantnagar Airport, a regional airport serving the city of Pantnagar in Uttarakhand, India.
  • D. 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.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e2db934819095556760c7d85e4d completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127a18c1081909d15aa7ed4b725e3 completed April 28, 2026, 9:33 p.m.
Created at: April 16, 2026, 8:21 p.m.