Triple

T19411869
Position Surface form Disambiguated ID Type / Status
Subject Hospital Playlist E485605 entity
Predicate mainCastMember P5563 FINISHED
Object Jeon Mi-do
Jeon Mi-do is a South Korean actress and musical theatre performer best known for her breakout television role in the acclaimed drama series "Hospital Playlist."
 E1428562 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: Jeon Mi-do | Statement: [Hospital Playlist, mainCastMember, Jeon Mi-do]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jeon Mi-do
Context triple: [Hospital Playlist, mainCastMember, Jeon Mi-do]
  • A. Won Jin-ah
    Won Jin-ah is a South Korean actress known for her roles in television dramas and films, including the dark fantasy series "Hellbound."
  • B. Yu Jae-sun
    Yu Jae-sun is a film producer best known for producing the South Korean movie "Silenced."
  • C. Lee Hae-jin
    Lee Hae-jin is a South Korean entrepreneur and technologist best known as the founder and longtime leader of internet giant Naver Corporation.
  • D. Ahn Seo-hyun
    Ahn Seo-hyun is a South Korean actress best known internationally for her lead role in Bong Joon-ho’s film "Okja."
  • E. Yoon Ga-eun
    Yoon Ga-eun is a South Korean film director and screenwriter known for her sensitive, realistic portrayals of children and adolescence.
  • 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: Jeon Mi-do
Triple: [Hospital Playlist, mainCastMember, Jeon Mi-do]
Generated description
Jeon Mi-do is a South Korean actress and musical theatre performer best known for her breakout television role in the acclaimed drama series "Hospital Playlist."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jeon Mi-do
Target entity description: Jeon Mi-do is a South Korean actress and musical theatre performer best known for her breakout television role in the acclaimed drama series "Hospital Playlist."
  • A. Won Jin-ah
    Won Jin-ah is a South Korean actress known for her roles in television dramas and films, including the dark fantasy series "Hellbound."
  • B. Yu Jae-sun
    Yu Jae-sun is a film producer best known for producing the South Korean movie "Silenced."
  • C. Lee Hae-jin
    Lee Hae-jin is a South Korean entrepreneur and technologist best known as the founder and longtime leader of internet giant Naver Corporation.
  • D. Ahn Seo-hyun
    Ahn Seo-hyun is a South Korean actress best known internationally for her lead role in Bong Joon-ho’s film "Okja."
  • E. Yoon Ga-eun
    Yoon Ga-eun is a South Korean film director and screenwriter known for her sensitive, realistic portrayals of children and adolescence.
  • 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_69e62af681288190ba2ec52d5adb6a22 completed April 20, 2026, 1:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0875fdccac819092279075a0ba3a4c completed May 16, 2026, 1:49 p.m.
NEDg Description generation batch_6a087754af1481909a8ffa042aad2f42 completed May 16, 2026, 1:55 p.m.
NED2 Entity disambiguation (via description) batch_6a0877dcf9548190bd42db7a54aea824 completed May 16, 2026, 1:57 p.m.
Created at: April 10, 2026, 1:37 p.m.