Triple

T8450958
Position Surface form Disambiguated ID Type / Status
Subject Okja E199795 entity
Predicate stars P1956 FINISHED
Object Choi Woo-shik E412434 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: Choi Woo-shik | Statement: [Okja, stars, Choi Woo-shik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Choi Woo-shik
Context triple: [Okja, stars, Choi Woo-shik]
  • A. Choi Woo-shik chosen
    Choi Woo-shik is a South Korean-Canadian actor known for his versatile performances in acclaimed films and dramas, including his breakout international role in the Oscar-winning film "Parasite."
  • B. Choi Doo-ho
    Choi Doo-ho is a South Korean film producer known for his work on the critically acclaimed fantasy-adventure film "Okja."
  • C. Song Seung-whan
    Song Seung-whan is a South Korean producer, director, and actor best known internationally for directing the opening and closing ceremonies of the 2018 PyeongChang Winter Olympics.
  • D. Han Jin-won
    Han Jin-won is a South Korean screenwriter best known for co-writing the Academy Award–winning film "Parasite."
  • E. Lee Sun-kyun
    Lee Sun-kyun was a South Korean actor acclaimed for his versatile performances in film and television, notably in works like the Academy Award–winning film "Parasite" and the series "My Mister."
  • 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_69ca8318231881908fd1bc1c4d45d286 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe44815488190a912d63512e19af0 completed March 31, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef2fa85ac8190adb7ddeb672bc550 completed April 2, 2026, 10:51 p.m.
Created at: March 30, 2026, 6:09 p.m.