Triple

T12518651
Position Surface form Disambiguated ID Type / Status
Subject Yoo Hong Lim E299256 entity
Predicate name P16 FINISHED
Object Yoo Hong Lim E299256 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: Yoo Hong Lim | Statement: [Yoo Hong Lim, name, Yoo Hong Lim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yoo Hong Lim
Context triple: [Yoo Hong Lim, name, Yoo Hong Lim]
  • A. Yoo Hong Lim chosen
    Yoo Hong Lim is a South Korean academic who serves as the president of Seoul National University, one of the country’s most prestigious universities.
  • B. Kyoungwon Lim
    Kyoungwon Lim is a film producer best known for working on the animated feature "The Nut Job."
  • C. Soo-Yung Han
    Soo-Yung Han is the young daughter of a Chinese consul whose kidnapping repeatedly drives the central plot and emotional stakes of the Rush Hour film series.
  • D. Ko Yong Hui
    Ko Yong Hui was a North Korean dancer who became a de facto first lady and is best known as the mother of current leader Kim Jong Un.
  • E. Yuk Young-soo
    Yuk Young-soo was the respected First Lady of South Korea and wife of President Park Chung-hee, remembered for her charitable work and her assassination in 1974.
  • 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9545a2e188190bb92120df740003d completed April 10, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64bbd58b88190baeb99380babf64f completed May 2, 2026, 7:08 p.m.
Created at: April 8, 2026, 9:57 p.m.