Triple

T6248139
Position Surface form Disambiguated ID Type / Status
Subject District Courts of South Korea E139772 entity
Predicate hasSeatIn P3522 FINISHED
Object Cheongju E444728 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: Cheongju | Statement: [District Courts of South Korea, hasSeatIn, Cheongju]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cheongju
Context triple: [District Courts of South Korea, hasSeatIn, Cheongju]
  • A. Cheongju chosen
    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.
  • 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. Jeonju
    Jeonju is a historic city in southwestern South Korea known for its well-preserved Hanok Village, rich culinary traditions, and cultural heritage.
  • 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. 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_69c008b1c5088190ae6de2555fc05ad8 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0633a9a048190856d5247d3b28a2e completed March 22, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6eec399f8819096e1db3ff6abd280 completed March 27, 2026, 8:55 p.m.
Created at: March 22, 2026, 4:23 p.m.