Triple

T13750382
Position Surface form Disambiguated ID Type / Status
Subject Byung-hun Lee E330333 entity
Predicate spouse P13 FINISHED
Object Lee Min-jung
Lee Min-jung is a South Korean actress known for her roles in popular television dramas and films.
E1066017 NE FINISHED

How this triple was built (4 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 Min-jung | Statement: [Byung-hun Lee, spouse, Lee Min-jung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lee Min-jung
Context triple: [Byung-hun Lee, spouse, Lee Min-jung]
  • A. Kim Yoon-ok
    Kim Yoon-ok is the former First Lady of South Korea, known primarily as the wife of ex-president Lee Myung-bak.
  • B. Kim Sung-ae
    Kim Sung-ae was the second wife of North Korean leader Kim Il Sung and a prominent political figure who headed the country’s women’s organization.
  • C. Kim Ok-yun
    Kim Ok-yun was the wife of Yun Posun, the second President of South Korea.
  • D. Lee In-hee
    Lee In-hee is a South Korean businesswoman and heiress known as a prominent member of the Samsung founding family.
  • E. Shin Hye-sook
    Shin Hye-sook is a South Korean figure skating coach best known for working with Olympic champion Yuna Kim during her early development.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lee Min-jung
Triple: [Byung-hun Lee, spouse, Lee Min-jung]
Generated description
Lee Min-jung is a South Korean actress known for her roles in popular television dramas and films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lee Min-jung
Target entity description: Lee Min-jung is a South Korean actress known for her roles in popular television dramas and films.
  • A. Kim Yoon-ok
    Kim Yoon-ok is the former First Lady of South Korea, known primarily as the wife of ex-president Lee Myung-bak.
  • B. Kim Sung-ae
    Kim Sung-ae was the second wife of North Korean leader Kim Il Sung and a prominent political figure who headed the country’s women’s organization.
  • C. Kim Ok-yun
    Kim Ok-yun was the wife of Yun Posun, the second President of South Korea.
  • D. Lee In-hee
    Lee In-hee is a South Korean businesswoman and heiress known as a prominent member of the Samsung founding family.
  • E. Shin Hye-sook
    Shin Hye-sook is a South Korean figure skating coach best known for working with Olympic champion Yuna Kim during her early development.
  • F. None of above. chosen

Provenance (5 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_69d81c573f288190aa2403d484fa3d49 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02148c208190a882927905a861a6 completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0ded1e0819097ef42533357caf8 completed May 3, 2026, 9:40 p.m.
NEDg Description generation batch_69f7c1e73fb481909f89ab3c0e9fb7d0 completed May 3, 2026, 9:45 p.m.
NED2 Entity disambiguation (via description) batch_69f7c3396f7c8190987079bf24ac8695 completed May 3, 2026, 9:50 p.m.
Created at: April 9, 2026, 10:08 p.m.