Triple

T6566483
Position Surface form Disambiguated ID Type / Status
Subject Chungcheong region E153918 entity
Predicate hasProvinceCapital P3433 FINISHED
Object Hongseong
Hongseong is a town in South Korea that serves as the administrative capital of South Chungcheong Province.
 E624619 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: Hongseong | Statement: [Chungcheong region, hasProvinceCapital, Hongseong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hongseong
Context triple: [Chungcheong region, hasProvinceCapital, Hongseong]
  • A. Hanseong
    Hanseong was the historical name for Seoul when it served as the capital of the Joseon Dynasty in Korea.
  • B. Gwangmyeong
    Gwangmyeong is a city in South Korea known for its proximity to Seoul and attractions like the Gwangmyeong Cave, a former mine turned cultural and tourism complex.
  • C. Hwaseong
    Hwaseong is a city in Gyeonggi Province, South Korea, known for its rapid industrial growth and proximity to major urban centers like Suwon and Seoul.
  • D. Gyeongseong
    Gyeongseong was the Japanese colonial-era name for Seoul, which served as the administrative and political center of Korea under Japanese rule.
  • E. Seogwipo
    Seogwipo is a coastal city on South Korea’s Jeju Island known for its waterfalls, volcanic landscapes, and popular tourist attractions.
  • 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: Hongseong
Triple: [Chungcheong region, hasProvinceCapital, Hongseong]
Generated description
Hongseong is a town in South Korea that serves as the administrative capital of South Chungcheong Province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hongseong
Target entity description: Hongseong is a town in South Korea that serves as the administrative capital of South Chungcheong Province.
  • A. Hanseong
    Hanseong was the historical name for Seoul when it served as the capital of the Joseon Dynasty in Korea.
  • B. Gwangmyeong
    Gwangmyeong is a city in South Korea known for its proximity to Seoul and attractions like the Gwangmyeong Cave, a former mine turned cultural and tourism complex.
  • C. Hwaseong
    Hwaseong is a city in Gyeonggi Province, South Korea, known for its rapid industrial growth and proximity to major urban centers like Suwon and Seoul.
  • D. Gyeongseong
    Gyeongseong was the Japanese colonial-era name for Seoul, which served as the administrative and political center of Korea under Japanese rule.
  • E. Seogwipo
    Seogwipo is a coastal city on South Korea’s Jeju Island known for its waterfalls, volcanic landscapes, and popular tourist attractions.
  • 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_69c6880cb35881909b763eb0125236b9 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae5381e88190b44dc4440efdd8ae completed March 27, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7422f57848190901b31229825b9e2 completed March 28, 2026, 2:51 a.m.
NEDg Description generation batch_69c7431d2d5881909daf29caeef37d0d completed March 28, 2026, 2:55 a.m.
NED2 Entity disambiguation (via description) batch_69c743949cbc8190a797666c7d509a1c completed March 28, 2026, 2:57 a.m.
Created at: March 27, 2026, 1:52 p.m.