Triple

T5859948
Position Surface form Disambiguated ID Type / Status
Subject Jung Ho-yeon E130249 entity
Predicate partner P1136 FINISHED
Object Lee Dong-hwi
Lee Dong-hwi is a South Korean actor known for his roles in popular films and television dramas, including the hit series "Reply 1988."
E570494 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 Dong-hwi | Statement: [Jung Ho-yeon, partner, Lee Dong-hwi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lee Dong-hwi
Context triple: [Jung Ho-yeon, partner, Lee Dong-hwi]
  • A. Kim Je-hyuk
    Kim Je-hyuk is the naive yet kindhearted star baseball player who becomes an unlikely inmate protagonist in the South Korean television drama "Prison Playbook."
  • B. Ban Woo-hyun
    Ban Woo-hyun is one of the children of former UN Secretary-General Ban Ki-moon and his wife Yoo Soon-taek.
  • C. Jang Young-hwan
    Jang Young-hwan is a South Korean film producer best known for his work on the Academy Award–winning film "Parasite."
  • D. Lee Byung-chul
    Lee Byung-chul was a South Korean entrepreneur and industrialist best known as the founder of the Samsung business empire, which grew into one of the world’s largest conglomerates.
  • E. Koo In-hwoi
    Koo In-hwoi was a South Korean entrepreneur who built one of the country’s leading chaebols, the LG Group, helping pioneer its modern electronics and chemical industries.
  • 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 Dong-hwi
Triple: [Jung Ho-yeon, partner, Lee Dong-hwi]
Generated description
Lee Dong-hwi is a South Korean actor known for his roles in popular films and television dramas, including the hit series "Reply 1988."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lee Dong-hwi
Target entity description: Lee Dong-hwi is a South Korean actor known for his roles in popular films and television dramas, including the hit series "Reply 1988."
  • A. Kim Je-hyuk
    Kim Je-hyuk is the naive yet kindhearted star baseball player who becomes an unlikely inmate protagonist in the South Korean television drama "Prison Playbook."
  • B. Ban Woo-hyun
    Ban Woo-hyun is one of the children of former UN Secretary-General Ban Ki-moon and his wife Yoo Soon-taek.
  • C. Jang Young-hwan
    Jang Young-hwan is a South Korean film producer best known for his work on the Academy Award–winning film "Parasite."
  • D. Lee Byung-chul
    Lee Byung-chul was a South Korean entrepreneur and industrialist best known as the founder of the Samsung business empire, which grew into one of the world’s largest conglomerates.
  • E. Koo In-hwoi
    Koo In-hwoi was a South Korean entrepreneur who built one of the country’s leading chaebols, the LG Group, helping pioneer its modern electronics and chemical industries.
  • 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_69c0084f3bb08190a7720f55f7aa4252 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0358790b88190a5e3c6473172dc53 completed March 22, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c13540fa788190a09a509267bdb147 completed March 23, 2026, 12:42 p.m.
NEDg Description generation batch_69c137c122d4819089c6ffc2e0cbaf54 completed March 23, 2026, 12:53 p.m.
NED2 Entity disambiguation (via description) batch_69c138247e2c8190b6c2aabbd36ad9c0 completed March 23, 2026, 12:55 p.m.
Created at: March 22, 2026, 3:56 p.m.