Triple

T5029598
Position Surface form Disambiguated ID Type / Status
Subject Seong Gi-hun E113262 entity
Predicate notableRelationship P1481 FINISHED
Object Kang Sae-byeok E116287 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: Kang Sae-byeok | Statement: [Seong Gi-hun, notableRelationship, Kang Sae-byeok]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kang Sae-byeok
Context triple: [Seong Gi-hun, notableRelationship, Kang Sae-byeok]
  • A. Kang Sae-byeok chosen
    Kang Sae-byeok is a North Korean defector and pickpocket who becomes one of the central, emotionally resonant contestants in the deadly survival competition of the South Korean series "Squid Game."
  • B. Jung Jang-seon
    Jung Jang-seon is a South Korean politician serving as the mayor of the city of Pyeongtaek.
  • C. Kwak Sin-ae
    Kwak Sin-ae is a South Korean film producer best known for producing the Academy Award–winning film "Parasite."
  • D. Heo Jeong
    Heo Jeong was a South Korean politician who served as prime minister and played a significant role in the country’s early post-war democratic politics.
  • E. Cha Jeong-in
    Cha Jeong-in is a South Korean academic who serves as the president of Pusan National University.
  • 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_69bd443775e48190a646ffbfc4334723 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd739099a0819099c6201d4e1c5ee2 completed March 20, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf219bdd208190990db4b0fa89066a completed March 21, 2026, 10:54 p.m.
Created at: March 20, 2026, 1:36 p.m.