Triple

T10730581
Position Surface form Disambiguated ID Type / Status
Subject Lee Myung-bak E253061 entity
Predicate name P16 FINISHED
Object Lee Myung-bak E253061 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 Myung-bak | Statement: [Lee Myung-bak, name, Lee Myung-bak]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lee Myung-bak
Context triple: [Lee Myung-bak, name, Lee Myung-bak]
  • A. Lee Myung-bak chosen
    Lee Myung-bak is a South Korean businessman-turned-politician who served as the President of South Korea from 2008 to 2013.
  • B. Roh Moo-hyun
    Roh Moo-hyun was a South Korean human rights lawyer-turned-politician who served as the country’s president from 2003 to 2008, known for his reformist agenda and efforts to engage North Korea.
  • C. 김대중
    김대중은 대한민국의 제15대 대통령으로, 민주화 운동과 남북 화해 정책(햇볕정책)을 주도해 노벨 평화상을 수상한 정치인이다.
  • D. John Kim
    John Kim is an Australian actor best known for his role as Ezekiel Jones in the fantasy-adventure television series "The Librarians."
  • E. John Kim
    John Kim is a prominent mechanical engineer and researcher renowned for his pioneering work in computational fluid dynamics and turbulence modeling.
  • 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_69d6aa5d8be481909a43218b2bfdbe95 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d70fcb1cd881909635def59ad5d19c completed April 9, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbda1d1b108190a47b46661bc85b2d completed April 12, 2026, 5:45 p.m.
Created at: April 8, 2026, 9:14 p.m.