Triple

T8525621
Position Surface form Disambiguated ID Type / Status
Subject 북구 E201807 entity
Predicate usedAsDistrictNameIn P50586 FINISHED
Object 청주시 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: 청주시 | Statement: [북구, usedAsDistrictNameIn, 청주시]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 청주시
Context triple: [북구, usedAsDistrictNameIn, 청주시]
  • A. Jecheon
    Jecheon is a city in North Chungcheong Province, South Korea, known as a regional transport hub surrounded by mountains and lakes.
  • B. 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.
  • C. 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.
  • D. Chuncheon
    Chuncheon is a city in northeastern South Korea known for its lakes, surrounding mountains, and status as the capital of Gangwon Province.
  • E. Daejeon
    Daejeon is a major city in central South Korea known as a hub for science, technology, and research institutions.
  • 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_69ca83228b24819085d22e7dc99f5d94 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc4578d9c8819096b3853d01c3ec11 completed March 31, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4e975d7c8190a7a1fc25c1d67a6f completed April 2, 2026, 11:10 a.m.
Created at: March 30, 2026, 6:16 p.m.