Triple

T7547396
Position Surface form Disambiguated ID Type / Status
Subject USS United States E178440 entity
Predicate builtAt P283 FINISHED
Object Philadelphia, Pennsylvania 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: Philadelphia, Pennsylvania | Statement: [USS United States, builtAt, Philadelphia, Pennsylvania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philadelphia, Pennsylvania
Context triple: [USS United States, builtAt, Philadelphia, Pennsylvania]
  • 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_69c69f2cbe08819088f9eb0c03ef529b completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f89a7b2c8190b2ca57edbb4f0390 completed March 27, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c856a8312881908a86c30706283a9c completed March 28, 2026, 10:31 p.m.
Created at: March 27, 2026, 3:49 p.m.