Triple

T20748118
Position Surface form Disambiguated ID Type / Status
Subject Jinju-si E510642 entity
Predicate romanizationMcCuneReischauer P23170 FINISHED
Object Chinju-si NE NERFINISHED

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: Chinju-si | Statement: [Jinju-si, romanizationMcCuneReischauer, Chinju-si]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chinju-si
Context triple: [Jinju-si, romanizationMcCuneReischauer, Chinju-si]
  • A. Jinju-si chosen
    Jinju-si is a city in South Gyeongsang Province, South Korea, known for its historic Jinju Fortress and the annual Namgang Yudeung (Lantern) Festival.
  • B. Gijeon
    Gijeon is an alternative name for the Seoul Capital Area, the densely populated metropolitan region surrounding South Korea’s capital city.
  • C. Chuncheon
    Chuncheon is a city in northeastern South Korea known for its lakes, surrounding mountains, and status as the capital of Gangwon Province.
  • D. Jecheon
    Jecheon is a city in North Chungcheong Province, South Korea, known as a regional transport hub surrounded by mountains and lakes.
  • E. Kyŏngju-si
    Kyŏngju-si is a historic coastal city in southeastern South Korea renowned for its rich Silla Dynasty heritage, ancient temples, and numerous UNESCO World Heritage sites.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4c845e88190b4c5f3ae79291182 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c226fbf881909794eff3ee9e206b completed April 21, 2026, 12:17 a.m.
Created at: April 16, 2026, 12:33 p.m.