Triple

T6802924
Position Surface form Disambiguated ID Type / Status
Subject Bumin Campus E156229 entity
Predicate region P40 FINISHED
Object Yeongnam E29096 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: Yeongnam | Statement: [Bumin Campus, region, Yeongnam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yeongnam
Context triple: [Bumin Campus, region, Yeongnam]
  • A. Anseongcheon
    Anseongcheon is a river in South Korea that flows through the city of Pyeongtaek in Gyeonggi Province.
  • B. Minho region
    The Minho region is a historic and culturally rich area in northwest Portugal, known for its lush green landscapes, traditional cuisine, and production of Vinho Verde wine.
  • C. Yeongnam region chosen
    The Yeongnam region is a major southeastern area of South Korea encompassing key cities such as Busan and Daegu, known for its dense population, industry, and distinct cultural identity.
  • D. Myeongneung
    Myeongneung is one of the royal burial sites from Korea’s Joseon Dynasty, forming part of the UNESCO-listed Royal Tombs complex.
  • E. Nam-gu
    Nam-gu is a central urban district of Daegu in South Korea, known for its residential neighborhoods, commercial areas, and educational institutions.
  • 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_69c68826e6a48190a3d220b541e639de completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2e714d4819084c8109c4de7de72 completed March 27, 2026, 6:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723d525bc8190aaf2390d690dc6a6 completed March 28, 2026, 12:41 a.m.
Created at: March 27, 2026, 2:16 p.m.