Triple

T19410690
Position Surface form Disambiguated ID Type / Status
Subject Silenced E485577 entity
Predicate editedBy P1954 FINISHED
Object Kim Sang-bum
Kim Sang-bum is a South Korean film editor known for his work on numerous acclaimed Korean movies.
E1390635 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: Kim Sang-bum | Statement: [Silenced, editedBy, Kim Sang-bum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kim Sang-bum
Context triple: [Silenced, editedBy, Kim Sang-bum]
  • A. Kim Jeong-suk
    Kim Jeong-suk is best known as the wife of South Korean general Paik Sun-yup, a prominent military figure during and after the Korean War.
  • B. Kim Hong-gul
    Kim Hong-gul is a South Korean politician and the son of former President and Nobel Peace Prize laureate Kim Dae-jung.
  • C. Kim Dong-wook
    Kim Dong-wook is a composer known for creating the musical score for the South Korean dark fantasy series "Hellbound."
  • D. Kim Won-bong
    Kim Won-bong was a prominent Korean independence activist and nationalist leader who organized militant resistance against Japanese colonial rule in the early 20th century.
  • E. Park Won-soon
    Park Won-soon was a prominent South Korean lawyer, civic activist, and politician who served as the long-time progressive mayor of Seoul until his death in 2020.
  • 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: Kim Sang-bum
Triple: [Silenced, editedBy, Kim Sang-bum]
Generated description
Kim Sang-bum is a South Korean film editor known for his work on numerous acclaimed Korean movies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kim Sang-bum
Target entity description: Kim Sang-bum is a South Korean film editor known for his work on numerous acclaimed Korean movies.
  • A. Kim Jeong-suk
    Kim Jeong-suk is best known as the wife of South Korean general Paik Sun-yup, a prominent military figure during and after the Korean War.
  • B. Kim Hong-gul
    Kim Hong-gul is a South Korean politician and the son of former President and Nobel Peace Prize laureate Kim Dae-jung.
  • C. Kim Dong-wook
    Kim Dong-wook is a composer known for creating the musical score for the South Korean dark fantasy series "Hellbound."
  • D. Kim Won-bong
    Kim Won-bong was a prominent Korean independence activist and nationalist leader who organized militant resistance against Japanese colonial rule in the early 20th century.
  • E. Park Won-soon
    Park Won-soon was a prominent South Korean lawyer, civic activist, and politician who served as the long-time progressive mayor of Seoul until his death in 2020.
  • 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_69d8e8d5162481909db12435d9535c1a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e62af4cc0c81909056b5e2ee574ab1 completed April 20, 2026, 1:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07ab7e0d4081909296ab9498e7996f completed May 15, 2026, 11:25 p.m.
NEDg Description generation batch_6a07acb892408190bd5e927cad3343ec completed May 15, 2026, 11:31 p.m.
NED2 Entity disambiguation (via description) batch_6a07ad2377488190b4f52c72a9a5d196 completed May 15, 2026, 11:32 p.m.
Created at: April 10, 2026, 1:37 p.m.