Triple

T6799233
Position Surface form Disambiguated ID Type / Status
Subject Upsal station E156138 entity
Predicate hasBorough P300 FINISHED
Object City of Philadelphia E171 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: City of Philadelphia | Statement: [Upsal station, hasBorough, City of Philadelphia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Philadelphia
Context triple: [Upsal station, hasBorough, City of Philadelphia]
  • A. Philadelphia
    Philadelphia is a 1993 American legal drama film that broke ground in mainstream cinema for its portrayal of HIV/AIDS, homophobia, and discrimination in the workplace.
  • B. Philadelphia
    Philadelphia was the ancient Greco-Roman name of the city now known as Amman, the capital of Jordan.
  • C. Philadelphia
    Philadelphia is a small town located in Loudon County, Tennessee, known for its rural character and historic Southern charm.
  • D. Philadelphia chosen
    Philadelphia is a major historic U.S. city in Pennsylvania known for its role in the American Revolution, iconic landmarks like Independence Hall and the Liberty Bell, and its rich cultural and academic institutions.
  • E. Filadelfia
    Filadelfia is a small municipality and town located in the Caldas Department of Colombia, known for its coffee-growing economy in the Andean region.
  • 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_69c6881844448190a65822d9b39d7f88 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2cb6b2881909b30bb8020a9d3bf completed March 27, 2026, 6:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72f86e9848190958e8f7a195fd20b completed March 28, 2026, 1:31 a.m.
Created at: March 27, 2026, 2:15 p.m.