Triple

T17617506
Position Surface form Disambiguated ID Type / Status
Subject Juanita M. Kreps E429122 entity
Predicate familyName P18 FINISHED
Object Kreps 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: Kreps | Statement: [Juanita M. Kreps, familyName, Kreps]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kreps
Context triple: [Juanita M. Kreps, familyName, Kreps]
  • A. Kreps chosen
    Kreps is the surname of David M. Kreps, an influential American economist known for his work in game theory and microeconomic theory.
  • B. Arsène
    Arsène is the iconic, phantom-thief–themed starting Persona of Joker in Persona 5, embodying rebellion and stylish vigilante justice.
  • C. Didier
    Didier is a masculine given name of French origin, notably borne by Ivorian football legend Didier Drogba.
  • D. Emrick
    Emrick is the surname of Mike "Doc" Emrick, a renowned American sportscaster best known for his long career as the lead play-by-play announcer for National Hockey League broadcasts.
  • E. Luke Geissbühler
    Luke Geissbühler is an American cinematographer known for his work on feature films, documentaries, and commercials, including the satirical comedy "Borat: Cultural Learnings of America for Make Benefit Glorious Nation of Kazakhstan."
  • 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_69d889e1c6148190ba76241e74688f8b completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46d33a2b081908deecee773c333af completed April 19, 2026, 5:50 a.m.
Created at: April 10, 2026, 5:51 a.m.