Triple

T23218577
Position Surface form Disambiguated ID Type / Status
Subject Park Bin-na E580818 entity
Predicate notableStudent P4838 FINISHED
Object Yuna Kim 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: Yuna Kim | Statement: [Park Bin-na, notableStudent, Yuna Kim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yuna Kim
Context triple: [Park Bin-na, notableStudent, Yuna Kim]
  • A. Yuna Kim chosen
    Yuna Kim is a South Korean figure skating legend and Olympic champion widely celebrated for her technical excellence, artistry, and global impact on the sport.
  • B. Alice Kim
    Alice Kim is an American former waitress and actress best known as the ex-wife of actor Nicolas Cage.
  • C. Nellie Kim
    Nellie Kim is a former Soviet artistic gymnast renowned for her multiple Olympic gold medals in the 1970s and for pioneering difficult tumbling and vaulting skills.
  • D. Saemi Kim
    Saemi Kim is a film and television producer known for her work behind the scenes bringing scripted projects to fruition.
  • E. Jacqueline Kim
    Jacqueline Kim is an American actress and filmmaker known for her roles in films such as "Volcano," "Star Trek: Generations," and "Charlotte Sometimes."
  • 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_69f191675de48190858907872a065c56 completed April 29, 2026, 5:04 a.m.
Created at: April 17, 2026, 4:08 p.m.