Triple

T5949237
Position Surface form Disambiguated ID Type / Status
Subject O Yeong-su E132355 entity
Predicate nativeName P15 FINISHED
Object 오영수
오영수는 넷플릭스 드라마 「오징어 게임」에서의 노인 참가자 ‘오일남’ 역으로 세계적인 주목을 받은 대한민국의 배우이다.
E559607 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: 오영수 | Statement: [O Yeong-su, nativeName, 오영수]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 오영수
Context triple: [O Yeong-su, nativeName, 오영수]
  • A. Kang Pan-sok
    Kang Pan-sok was a Korean woman best known as the mother of North Korea’s founding leader Kim Il Sung and is venerated in North Korean state mythology.
  • B. Shin Young-soo
    Shin Young-soo is a South Korean physician and public health expert who served as the World Health Organization’s Regional Director for the Western Pacific.
  • C. Suh Yun-bok
    Suh Yun-bok was a South Korean long-distance runner best known for winning the 1947 Boston Marathon and later serving as a symbolic sports figure in Korea.
  • D. Jeon Bong-jun
    Jeon Bong-jun was a prominent late 19th-century Korean peasant leader who spearheaded the Donghak Peasant Rebellion against corrupt officials and foreign influence in Joseon Korea.
  • E. Joseph Kyeong Kap-ryong
    Joseph Kyeong Kap-ryong was a South Korean Roman Catholic prelate who served as bishop and later bishop emeritus of the Diocese of Daejeon.
  • 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: 오영수
Triple: [O Yeong-su, nativeName, 오영수]
Generated description
오영수는 넷플릭스 드라마 「오징어 게임」에서의 노인 참가자 ‘오일남’ 역으로 세계적인 주목을 받은 대한민국의 배우이다.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 오영수
Target entity description: 오영수는 넷플릭스 드라마 「오징어 게임」에서의 노인 참가자 ‘오일남’ 역으로 세계적인 주목을 받은 대한민국의 배우이다.
  • A. Kang Pan-sok
    Kang Pan-sok was a Korean woman best known as the mother of North Korea’s founding leader Kim Il Sung and is venerated in North Korean state mythology.
  • B. Shin Young-soo
    Shin Young-soo is a South Korean physician and public health expert who served as the World Health Organization’s Regional Director for the Western Pacific.
  • C. Suh Yun-bok
    Suh Yun-bok was a South Korean long-distance runner best known for winning the 1947 Boston Marathon and later serving as a symbolic sports figure in Korea.
  • D. Jeon Bong-jun
    Jeon Bong-jun was a prominent late 19th-century Korean peasant leader who spearheaded the Donghak Peasant Rebellion against corrupt officials and foreign influence in Joseon Korea.
  • E. Joseph Kyeong Kap-ryong
    Joseph Kyeong Kap-ryong was a South Korean Roman Catholic prelate who served as bishop and later bishop emeritus of the Diocese of Daejeon.
  • 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_69c00869d3308190af89b2453e0f7546 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0397deea08190b9397d0413740300 completed March 22, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3c4120c8190bab97f91a7bc7030 completed March 23, 2026, 6:55 a.m.
NEDg Description generation batch_69c0f66f787c81909f76556d8e688a9a completed March 23, 2026, 8:14 a.m.
NED2 Entity disambiguation (via description) batch_69c0f73744b08190b82c538fa723c42a completed March 23, 2026, 8:17 a.m.
Created at: March 22, 2026, 4:02 p.m.