Triple

T9780302
Position Surface form Disambiguated ID Type / Status
Subject Scarlett Johansson as Silken Floss E237349 entity
Predicate settingOfWork P15236 FINISHED
Object Central City E403879 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: Central City | Statement: [Scarlett Johansson as Silken Floss, settingOfWork, Central City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Central City
Context triple: [Scarlett Johansson as Silken Floss, settingOfWork, Central City]
  • A. Central City
    Central City is a major urban area in New Orleans known for its historic neighborhoods, cultural diversity, and role in the city’s social and commercial life.
  • B. Central City chosen
    Central City is the primary fictional metropolis in the DC Comics universe known as the home of the superhero The Flash.
  • C. Central City
    Central City is the fictional Midwestern town that serves as the primary backdrop for the classic American sitcom "The Many Loves of Dobie Gillis."
  • D. Central City
    Central City is a small town in Linn County, Iowa, known for its rural Midwestern character and community-oriented lifestyle.
  • E. Central City
    Central City was the former name of Santa Maria, a city in California’s Central Coast region known for agriculture and wine production.
  • 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_69ca84d975a08190aab25b02a89bdab3 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda1b0b15881909ef52d0156148c59 completed April 1, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc4bb6008190b5111d42ceef52b7 completed April 5, 2026, 2:43 a.m.
Created at: March 30, 2026, 8:27 p.m.