Triple

T8277794
Position Surface form Disambiguated ID Type / Status
Subject House of Yi E193589 entity
Predicate capitalDuringRule P234 FINISHED
Object Hanseong E514441 NE FINISHED

How this triple was built (2 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: Hanseong | Statement: [House of Yi, capitalDuringRule, Hanseong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanseong
Context triple: [House of Yi, capitalDuringRule, Hanseong]
  • A. Hanseong chosen
    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. Hongseong
    Hongseong is a town in South Korea that serves as the administrative capital of South Chungcheong Province.
  • D. Kaesong
    Kaesong is a historic city in present-day North Korea that served as the capital of the medieval Korean kingdom of Goryeo and remains known for its cultural heritage and traditional architecture.
  • E. Jincheon
    Jincheon is a county in North Chungcheong Province, South Korea, known for its agricultural production and growing role as a logistics and industrial hub.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca82e217a48190880695635c44b2ed completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb79ebb6b88190bc777b8bd72fcdbc completed March 31, 2026, 7:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfab01c58c81909148dacad2dc7667 completed April 3, 2026, 11:56 a.m.
Created at: March 30, 2026, 5:51 p.m.