Triple

T1557736
Position Surface form Disambiguated ID Type / Status
Subject Suyeong District E33247 entity
Predicate borders P224 FINISHED
Object Haeundae District E199270 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: Haeundae District | Statement: [Suyeong District, borders, Haeundae District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haeundae District
Context triple: [Suyeong District, borders, Haeundae District]
  • A. Haeundae District chosen
    Haeundae District is a coastal district of Busan, South Korea, famous for its popular beach, tourism, and cultural attractions.
  • B. Dongnae District
    Dongnae District is a historic and central administrative district of Busan, South Korea, known for its hot springs and cultural heritage sites.
  • C. Seocho District
    Seocho District is a major affluent ward in southern Seoul, South Korea, known for its legal institutions, upscale residential areas, and proximity to the Gangnam business district.
  • D. Busanjin District
    Busanjin District is a central urban district of Busan, South Korea, known as a major commercial and transportation hub of the city.
  • E. Yeonje District
    Yeonje District is an urban administrative district located in the central area of Busan, South Korea, known for its residential neighborhoods and transportation links.
  • 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_69a885ef9cf48190b0af0f5ce3d02231 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9088355048190adad5ea2bb558d13 completed March 5, 2026, 4:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeac0be308190a12ba8e79589dead completed March 8, 2026, 9:31 p.m.
Created at: March 4, 2026, 7:27 p.m.