Triple

T6903399
Position Surface form Disambiguated ID Type / Status
Subject Nurimaru APEC House E159546 entity
Predicate operator P179 FINISHED
Object City of Busan E4279 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: City of Busan | Statement: [Nurimaru APEC House, operator, City of Busan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Busan
Context triple: [Nurimaru APEC House, operator, City of Busan]
  • A. Busan, South Korea
    Busan, South Korea is the country’s second-largest city and a major coastal hub known for its busy port, beaches, and international film festival.
  • B. Pohang
    Pohang is a major industrial and port city in South Korea, best known as the home of the global steelmaker POSCO and a key hub on the country’s east coast.
  • C. Busan chosen
    Busan is South Korea’s second-largest city and a major international port known for its bustling harbor, beaches, and coastal scenery.
  • D. Jinju-si
    Jinju-si is a city in South Gyeongsang Province, South Korea, known for its historic Jinju Fortress and the annual Namgang Yudeung (Lantern) Festival.
  • E. Changwon
    Changwon is a major industrial and administrative city in South Gyeongsang Province, South Korea, known for its planned urban layout and role as a regional government and manufacturing 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_69c6883822e0819091e321526f20ae0a completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d988a5b48190a9238047e86f314c completed March 27, 2026, 7:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1e3d6191c8190adb41feec1bfa76e completed April 5, 2026, 4:23 a.m.
Created at: March 27, 2026, 2:25 p.m.