Triple

T22928574
Position Surface form Disambiguated ID Type / Status
Subject William Larimer Mellon Sr. E569373 entity
Predicate associatedWith P37 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: [William Larimer Mellon Sr., associatedWith, Pittsburgh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pittsburgh
Context triple: [William Larimer Mellon Sr., associatedWith, 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. Pittsburg μSA
    Pittsburg μSA is a U.S. micropolitan statistical area centered on Pittsburg, Kansas, used by the Census Bureau for regional demographic and economic analysis.
  • D. PGH
    PGH is the IATA airport code for Pantnagar Airport, a regional airport serving the city of Pantnagar in Uttarakhand, India.
  • E. 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.
  • 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_69e2458f7d008190901dccbaebeaba24 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f180db6db88190bc8efb691dcdfdba completed April 29, 2026, 3:54 a.m.
Created at: April 17, 2026, 3:44 p.m.