Triple

T19116345
Position Surface form Disambiguated ID Type / Status
Subject Oh E467916 entity
Predicate hasNotableBearer P458 FINISHED
Object Oh Jung-se
Oh Jung-se is a South Korean actor acclaimed for his versatile supporting and character roles in film and television dramas.
E1378142 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: Oh Jung-se | Statement: [Oh, hasNotableBearer, Oh Jung-se]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oh Jung-se
Context triple: [Oh, hasNotableBearer, Oh Jung-se]
  • A. Oh Jae-won
    Oh Jae-won is a South Korean former professional baseball infielder who played in the KBO League, most notably for the Doosan Bears.
  • B. Kim Dong-wook
    Kim Dong-wook is a composer known for creating the musical score for the South Korean dark fantasy series "Hellbound."
  • C. Min Kyung-ho
    Min Kyung-ho is a Korean individual notable primarily for bearing the given name "Min."
  • D. Jung Jae-young
    Jung Jae-young is a South Korean actor known for his versatile performances in both critically acclaimed films and popular television dramas.
  • E. Jin Kyeong-hun
    Jin Kyeong-hun is a central character in the South Korean dark fantasy series "Hellbound," depicted as a determined detective entangled in the mysterious and terrifying supernatural decrees that suddenly begin condemning people to hell.
  • 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: Oh Jung-se
Triple: [Oh, hasNotableBearer, Oh Jung-se]
Generated description
Oh Jung-se is a South Korean actor acclaimed for his versatile supporting and character roles in film and television dramas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Oh Jung-se
Target entity description: Oh Jung-se is a South Korean actor acclaimed for his versatile supporting and character roles in film and television dramas.
  • A. Oh Jae-won
    Oh Jae-won is a South Korean former professional baseball infielder who played in the KBO League, most notably for the Doosan Bears.
  • B. Kim Dong-wook
    Kim Dong-wook is a composer known for creating the musical score for the South Korean dark fantasy series "Hellbound."
  • C. Min Kyung-ho
    Min Kyung-ho is a Korean individual notable primarily for bearing the given name "Min."
  • D. Jung Jae-young
    Jung Jae-young is a South Korean actor known for his versatile performances in both critically acclaimed films and popular television dramas.
  • E. Jin Kyeong-hun
    Jin Kyeong-hun is a central character in the South Korean dark fantasy series "Hellbound," depicted as a determined detective entangled in the mysterious and terrifying supernatural decrees that suddenly begin condemning people to hell.
  • 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_69d8dd06a26481908039e2a1bae8c597 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e3984bf48190818fa2b01b75decb completed April 20, 2026, 8:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a07403a9e048190a158e9b1896de6e2 completed May 15, 2026, 3:48 p.m.
NEDg Description generation batch_6a074145c3f48190a052c8d8fac0f2be completed May 15, 2026, 3:52 p.m.
NED2 Entity disambiguation (via description) batch_6a0741fc21888190913ce428cb176ffd completed May 15, 2026, 3:55 p.m.
Created at: April 10, 2026, 12:05 p.m.