Triple

T6784125
Position Surface form Disambiguated ID Type / Status
Subject 부산광역시 북구 E155757 entity
Predicate borderedBy P224 FINISHED
Object 부산광역시 강서구 E178990 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: 부산광역시 강서구 | Statement: [부산광역시 북구, borderedBy, 부산광역시 강서구]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 부산광역시 강서구
Context triple: [부산광역시 북구, borderedBy, 부산광역시 강서구]
  • A. 부산광역시 북구
    부산광역시 북구는 대한민국 부산광역시 북부에 위치한 행정구로, 주거 지역과 교육·상업 시설이 혼재한 도심 외곽 지역이다.
  • B. Seo District, Busan
    Seo District, Busan is a central administrative and residential area of Busan, South Korea, known for its urban neighborhoods, commercial zones, and connectivity via the Busan Metro.
  • C. Haeundae District, Busan
    Haeundae District, Busan is a coastal district in South Korea renowned for its popular beach, luxury hotels, and role as a major tourism and cultural hub of the city.
  • D. Gangseo District, Busan chosen
    Gangseo District is a coastal administrative district in western Busan, South Korea, known for its industrial complexes, port facilities, and Gimhae International Airport.
  • E. Geumjeong District, Busan
    Geumjeong District is a northeastern district of Busan, South Korea, known for its major university presence and proximity to the scenic Geumjeongsan mountain area.
  • 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_69c688162bf8819088b664b5c3b5be7a completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d28bdc3c8190aa60616d89db66ed completed March 27, 2026, 6:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c712d5557881909614819deb335534 completed March 27, 2026, 11:29 p.m.
Created at: March 27, 2026, 2:14 p.m.