Triple

T23212087
Position Surface form Disambiguated ID Type / Status
Subject Gail E580622 entity
Predicate setting P1957 FINISHED
Object Basin City 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: Basin City | Statement: [Gail, setting, Basin City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Basin City
Context triple: [Gail, setting, Basin City]
  • A. Basin City chosen
    Basin City is the gritty, crime-ridden fictional metropolis that serves as the primary setting for Frank Miller’s Sin City graphic novels and their film adaptations.
  • B. Limestone City
    Limestone City is a nickname for Kingston, Ontario, reflecting its many historic buildings constructed from local limestone.
  • C. Shell City
    Shell City is a fictional gift shop and tourist attraction in The SpongeBob SquarePants Movie, infamous as the perilous destination at the end of the ocean where sea creatures are taken and dried.
  • D. Barb City
    Barb City is the nickname of DeKalb, Illinois, reflecting its historical prominence in the barbed wire industry.
  • E. Lumber City
    Lumber City is the historic nickname of North Tonawanda, New York, reflecting its past prominence as a major center of the lumber industry.
  • 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_69e2460389408190be74f41d217799a9 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f191620378819096362252c3b819b6 completed April 29, 2026, 5:04 a.m.
Created at: April 17, 2026, 4:07 p.m.