Triple

T4992702
Position Surface form Disambiguated ID Type / Status
Subject Deoksugung E112169 entity
Predicate locatedOn P40 FINISHED
Object Sejong-daero
Sejong-daero is a major thoroughfare in central Seoul, South Korea, known for its historical landmarks, government buildings, and cultural significance.
 E502846 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: Sejong-daero | Statement: [Deoksugung, locatedOn, Sejong-daero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sejong-daero
Context triple: [Deoksugung, locatedOn, Sejong-daero]
  • A. Nonhyeon-dong
    Nonhyeon-dong is a neighborhood in Seoul, South Korea, known for its mix of residential areas, commercial streets, and proximity to major business and shopping districts.
  • B. Yangjeong-dong
    Yangjeong-dong is a neighborhood (dong) located within Busanjin District in the city of Busan, South Korea.
  • C. Cheongnyong-dong
    Cheongnyong-dong is a neighborhood located within Geumjeong District in Busan, South Korea.
  • D. Cheonghak-dong
    Cheonghak-dong is a neighborhood within the city of Osan in Gyeonggi Province, South Korea.
  • E. Gocheon-dong
    Gocheon-dong is a neighborhood (dong) that forms part of the city of Osan in Gyeonggi Province, South Korea.
  • 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: Sejong-daero
Triple: [Deoksugung, locatedOn, Sejong-daero]
Generated description
Sejong-daero is a major thoroughfare in central Seoul, South Korea, known for its historical landmarks, government buildings, and cultural significance.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sejong-daero
Target entity description: Sejong-daero is a major thoroughfare in central Seoul, South Korea, known for its historical landmarks, government buildings, and cultural significance.
  • A. Nonhyeon-dong
    Nonhyeon-dong is a neighborhood in Seoul, South Korea, known for its mix of residential areas, commercial streets, and proximity to major business and shopping districts.
  • B. Yangjeong-dong
    Yangjeong-dong is a neighborhood (dong) located within Busanjin District in the city of Busan, South Korea.
  • C. Cheongnyong-dong
    Cheongnyong-dong is a neighborhood located within Geumjeong District in Busan, South Korea.
  • D. Cheonghak-dong
    Cheonghak-dong is a neighborhood within the city of Osan in Gyeonggi Province, South Korea.
  • E. Gocheon-dong
    Gocheon-dong is a neighborhood (dong) that forms part of the city of Osan in Gyeonggi Province, South Korea.
  • 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_69bd441be7bc8190b530362d427b97d2 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd729bb45081908d85891a9d9f4b71 completed March 20, 2026, 4:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69beef92c2d88190b56dbb48f1f97151 completed March 21, 2026, 7:20 p.m.
NEDg Description generation batch_69bef0761c208190bac06ff1f92c8224 completed March 21, 2026, 7:24 p.m.
NED2 Entity disambiguation (via description) batch_69bef14ca27c81909a5a44155c9ddaf9 completed March 21, 2026, 7:28 p.m.
Created at: March 20, 2026, 1:34 p.m.