Triple

T2013670
Position Surface form Disambiguated ID Type / Status
Subject Gyeonggi Province E43744 entity
Predicate hasCity P316 FINISHED
Object Gunpo
Gunpo is a small satellite city in South Korea’s Seoul Capital Area, known for its residential communities and convenient commuter access to Seoul.
 E426914 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: Gunpo | Statement: [Gyeonggi Province, hasCity, Gunpo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gunpo
Context triple: [Gyeonggi Province, hasCity, Gunpo]
  • A. Anseong
    Anseong is a city in Gyeonggi Province, South Korea, known for its traditional culture, agricultural heritage, and annual Baudeogi Festival.
  • B. Namyangju
    Namyangju is a city in South Korea known for its scenic natural landscapes, historical sites, and role as a suburban area within the Seoul metropolitan region.
  • C. Siheung
    Siheung is a coastal city in northwestern South Korea known for its industrial complexes, wetlands, and proximity to Seoul.
  • D. Uijeongbu
    Uijeongbu is a city in South Korea known as a suburban hub north of Seoul, featuring residential districts, commercial centers, and a history of hosting U.S. military bases.
  • E. Dangjin
    Dangjin is a coastal city in South Chungcheong Province, South Korea, known for its heavy industry, steel production, and port facilities on the Yellow Sea.
  • 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: Gunpo
Triple: [Gyeonggi Province, hasCity, Gunpo]
Generated description
Gunpo is a small satellite city in South Korea’s Seoul Capital Area, known for its residential communities and convenient commuter access to Seoul.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gunpo
Target entity description: Gunpo is a small satellite city in South Korea’s Seoul Capital Area, known for its residential communities and convenient commuter access to Seoul.
  • A. Anseong
    Anseong is a city in Gyeonggi Province, South Korea, known for its traditional culture, agricultural heritage, and annual Baudeogi Festival.
  • B. Namyangju
    Namyangju is a city in South Korea known for its scenic natural landscapes, historical sites, and role as a suburban area within the Seoul metropolitan region.
  • C. Siheung
    Siheung is a coastal city in northwestern South Korea known for its industrial complexes, wetlands, and proximity to Seoul.
  • D. Uijeongbu
    Uijeongbu is a city in South Korea known as a suburban hub north of Seoul, featuring residential districts, commercial centers, and a history of hosting U.S. military bases.
  • E. Dangjin
    Dangjin is a coastal city in South Chungcheong Province, South Korea, known for its heavy industry, steel production, and port facilities on the Yellow Sea.
  • 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_69a88716e9f08190946313fdc949e3cf completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb8b42d508190bf2b63132bb2ad77 completed March 7, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5b729cc34819093ebf3fac53d7a9d completed March 14, 2026, 7:29 p.m.
NEDg Description generation batch_69b5bb3af33081909f25c324b475e5f7 completed March 14, 2026, 7:47 p.m.
NED2 Entity disambiguation (via description) batch_69b5bba8d54081909feb5ebc5bace2d1 completed March 14, 2026, 7:48 p.m.
Created at: March 4, 2026, 7:37 p.m.