Triple

T10567316
Position Surface form Disambiguated ID Type / Status
Subject Pusanjin-gu E249383 entity
Predicate hasSubdivision P747 FINISHED
Object Gaya-dong E268196 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: Gaya-dong | Statement: [Pusanjin-gu, hasSubdivision, Gaya-dong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gaya-dong
Context triple: [Pusanjin-gu, hasSubdivision, Gaya-dong]
  • A. Gaya-dong chosen
    Gaya-dong is a neighborhood in Busan, South Korea, known as a residential and commercial area within the central urban zone of the city.
  • B. Yangsan-dong
    Yangsan-dong is a neighborhood (dong) within the city of Osan in Gyeonggi Province, South Korea.
  • C. Dangsan-dong
    Dangsan-dong is a neighborhood in western Seoul, South Korea, known for its residential areas, commercial facilities, and convenient access via major subway lines.
  • D. Danggam-dong
    Danggam-dong is a neighborhood (dong) within Busanjin District in Busan, South Korea, known primarily as a residential and commercial urban area.
  • E. Seo-dong
    Seo-dong is a neighborhood within Busan’s Geumjeong District in South Korea, known primarily as a residential area with local commerce and community facilities.
  • 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_69d381c8bd708190acf3d275c908251e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5272ef5848190b76d671ea2d26314 completed April 7, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3a8e98cac8190873af1a2cdb5c5a9 completed April 18, 2026, 3:53 p.m.
Created at: April 6, 2026, 12:36 p.m.