Triple

T7724525
Position Surface form Disambiguated ID Type / Status
Subject Ma Dong-seok E175095 entity
Predicate alsoKnownAs P39 FINISHED
Object Lee Dong-seok E684472 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: Lee Dong-seok | Statement: [Ma Dong-seok, alsoKnownAs, Lee Dong-seok]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lee Dong-seok
Context triple: [Ma Dong-seok, alsoKnownAs, Lee Dong-seok]
  • A. Ma Dong-seok chosen
    Ma Dong-seok is a South Korean-American actor best known internationally for his tough-guy roles in films like "Train to Busan" and "The Outlaws."
  • B. 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.
  • C. 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."
  • D. Han Jin-won
    Han Jin-won is a South Korean screenwriter best known for co-writing the Academy Award–winning film "Parasite."
  • E. Kim Swoo Geun
    Kim Swoo Geun was a prominent South Korean architect renowned for pioneering modern Korean architecture and shaping Seoul’s urban landscape in the mid-20th century.
  • 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_69c6995d541c81909eaa646b1a8369a9 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7031279708190a3a5fb64f9206974 completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8c7beffc48190b39048b6afc1d644 completed March 29, 2026, 6:33 a.m.
Created at: March 27, 2026, 4:05 p.m.