Triple

T16622906
Position Surface form Disambiguated ID Type / Status
Subject Danielle Panabaker as Caitlin Snow E403875 entity
Predicate cityOfActivity P24431 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: [Danielle Panabaker as Caitlin Snow, cityOfActivity, Central City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Central City
Context triple: [Danielle Panabaker as Caitlin Snow, cityOfActivity, 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_69d883897eb481909eaaa088ba9918d9 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3754f4f508190a5b4b8511623fcd4 completed April 18, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00918ae5f48190a85af2dfbe9708d4 completed May 10, 2026, 2:09 p.m.
Created at: April 10, 2026, 5:17 a.m.