Triple

T10730292
Position Surface form Disambiguated ID Type / Status
Subject Chungcheongbuk-do E253052 entity
Predicate hasCity P316 FINISHED
Object Jecheon E617846 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: Jecheon | Statement: [Chungcheongbuk-do, hasCity, Jecheon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jecheon
Context triple: [Chungcheongbuk-do, hasCity, Jecheon]
  • A. Jecheon chosen
    Jecheon is a city in North Chungcheong Province, South Korea, known as a regional transport hub surrounded by mountains and lakes.
  • B. Chungju
    Chungju is a city in North Chungcheong Province, South Korea, known for its agricultural surroundings, historical sites, and the Chungju Dam on the Namhan River.
  • C. Cheongju
    Cheongju is a major city in central South Korea that serves as the capital of North Chungcheong Province and an important regional administrative, educational, and transportation hub.
  • D. Icheon
    Icheon is a South Korean city renowned for its traditional ceramics and hot spring resorts.
  • E. Yeongcheon
    Yeongcheon is a city in southeastern South Korea known for its agricultural production and historical sites within North Gyeongsang Province.
  • 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_69d6aa5d8be481909a43218b2bfdbe95 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d70fca498881909b40163a138cfb98 completed April 9, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6f5b196bc8190a643f2b534497476 completed May 3, 2026, 7:13 a.m.
Created at: April 8, 2026, 9:14 p.m.