Triple

T5142010
Position Surface form Disambiguated ID Type / Status
Subject John Cho E115973 entity
Predicate birthName P65 FINISHED
Object Cho Yo-han
Cho Yo-han is the Korean birth name of John Cho, a Korean American actor best known for his roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
E516605 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: Cho Yo-han | Statement: [John Cho, birthName, Cho Yo-han]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cho Yo-han
Context triple: [John Cho, birthName, Cho Yo-han]
  • A. Jung Ho-yeon
    Jung Ho-yeon is a South Korean model-turned-actress who gained international fame for her breakout role in the Netflix survival drama series "Squid Game."
  • B. Oh Se-hoon
    Oh Se-hoon is a South Korean politician best known for serving multiple terms as the mayor of Seoul.
  • 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 Yong-ik
    Lee Yong-ik was a prominent Korean educator and nationalist who played a key role in modernizing education in Korea and helped establish Korea University as a leading institution of higher learning.
  • 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: Cho Yo-han
Triple: [John Cho, birthName, Cho Yo-han]
Generated description
Cho Yo-han is the Korean birth name of John Cho, a Korean American actor best known for his roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Cho Yo-han
Target entity description: Cho Yo-han is the Korean birth name of John Cho, a Korean American actor best known for his roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
  • A. Jung Ho-yeon
    Jung Ho-yeon is a South Korean model-turned-actress who gained international fame for her breakout role in the Netflix survival drama series "Squid Game."
  • B. Oh Se-hoon
    Oh Se-hoon is a South Korean politician best known for serving multiple terms as the mayor of Seoul.
  • 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 Yong-ik
    Lee Yong-ik was a prominent Korean educator and nationalist who played a key role in modernizing education in Korea and helped establish Korea University as a leading institution of higher learning.
  • 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_69bd44459a988190a772a5c2ec6a1965 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd787ff1c081909a6954aa76e12cbf completed March 20, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf330bc5c48190ad8ca1e413b6c68b completed March 22, 2026, 12:08 a.m.
NEDg Description generation batch_69bf33b60cac8190b62210b23ce90d06 completed March 22, 2026, 12:11 a.m.
NED2 Entity disambiguation (via description) batch_69bf341dab94819095fe429560cdbbc5 completed March 22, 2026, 12:13 a.m.
Created at: March 20, 2026, 1:43 p.m.