Triple

T889578
Position Surface form Disambiguated ID Type / Status
Subject Seoul E19209 entity
Predicate hasMayor P185 FINISHED
Object Oh Se-hoon
Oh Se-hoon is a South Korean politician best known for serving multiple terms as the mayor of Seoul.
 E105450 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 Se-hoon | Statement: [Seoul, hasMayor, Oh Se-hoon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Oh Se-hoon
Context triple: [Seoul, hasMayor, Oh Se-hoon]
  • A. 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.
  • B. 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.
  • C. Kim Jong-suk
    Kim Jong-suk was a Korean anti-Japanese guerrilla fighter and revered North Korean revolutionary figure, celebrated as the first wife of Kim Il Sung and mother of Kim Jong Il.
  • D. Lee Gon Toy
    Lee Gon Toy was the father of pioneering Chinese American actress Anna May Wong.
  • E. Peter Sohn
    Peter Sohn is an American animator, voice actor, and film director at Pixar known for his work on projects like "Ratatouille," "The Good Dinosaur," and "Elemental."
  • 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 Se-hoon
Triple: [Seoul, hasMayor, Oh Se-hoon]
Generated description
Oh Se-hoon is a South Korean politician best known for serving multiple terms as the mayor of Seoul.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Oh Se-hoon
Target entity description: Oh Se-hoon is a South Korean politician best known for serving multiple terms as the mayor of Seoul.
  • A. 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.
  • B. 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.
  • C. Kim Jong-suk
    Kim Jong-suk was a Korean anti-Japanese guerrilla fighter and revered North Korean revolutionary figure, celebrated as the first wife of Kim Il Sung and mother of Kim Jong Il.
  • D. Lee Gon Toy
    Lee Gon Toy was the father of pioneering Chinese American actress Anna May Wong.
  • E. Peter Sohn
    Peter Sohn is an American animator, voice actor, and film director at Pixar known for his work on projects like "Ratatouille," "The Good Dinosaur," and "Elemental."
  • 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_69a4939d37188190848be3d426ebc9ae completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4acff52008190ac2975c08ad29f54 completed March 1, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c023464481909759c457e87266ab completed March 4, 2026, 5:16 a.m.
NEDg Description generation batch_69a7c1509a8c81909b8cf074e1ce7169 completed March 4, 2026, 5:21 a.m.
NED2 Entity disambiguation (via description) batch_69a7c21dd42881908ac19fed7454d7a9 completed March 4, 2026, 5:24 a.m.
Created at: March 1, 2026, 7:39 p.m.