Triple

T11459691
Position Surface form Disambiguated ID Type / Status
Subject Jincheon County E271620 entity
Predicate capital P234 FINISHED
Object Jincheon-eup E445373 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: Jincheon-eup | Statement: [Jincheon County, capital, Jincheon-eup]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jincheon-eup
Context triple: [Jincheon County, capital, Jincheon-eup]
  • A. Jincheon chosen
    Jincheon is a county in North Chungcheong Province, South Korea, known for its agricultural production and growing role as a logistics and industrial hub.
  • B. Icheon
    Icheon is a South Korean city renowned for its traditional ceramics and hot spring resorts.
  • C. 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.
  • D. Geumwang-eup
    Geumwang-eup is a town-level administrative division in Eumseong County, located in North Chungcheong Province, South Korea.
  • E. 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.
  • 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_69d6aadff8888190a13f253f0d460874 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d822f2138081909408c7916cef99c9 completed April 9, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbac706dc4819093f06b368f03fe02 completed May 6, 2026, 9:02 p.m.
Created at: April 8, 2026, 9:35 p.m.