Triple

T23259353
Position Surface form Disambiguated ID Type / Status
Subject Banpo Bridge E581961 entity
Predicate name P16 FINISHED
Object Banpo Bridge NE NERFINISHED

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: Banpo Bridge | Statement: [Banpo Bridge, name, Banpo Bridge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Banpo Bridge
Context triple: [Banpo Bridge, name, Banpo Bridge]
  • A. Banpo Bridge chosen
    Banpo Bridge is a major double-deck bridge over the Han River in Seoul, South Korea, famous for its Moonlight Rainbow Fountain show.
  • B. Wonhyo Bridge
    Wonhyo Bridge is a major road bridge over the Han River in Seoul, South Korea, linking the Yeouido financial district with the southern part of the city.
  • C. Namhang Bridge
    Namhang Bridge is a major road bridge in Busan, South Korea, connecting Yeongdo Island with the mainland and serving as an important transportation and scenic landmark.
  • D. Yeongjong Bridge
    Yeongjong Bridge is a major South Korean cable-stayed bridge that links the mainland city of Incheon to Yeongjong Island, home to Incheon International Airport.
  • E. Seogang Bridge
    Seogang Bridge is a major road bridge in Seoul, South Korea, spanning the Han River and linking Yeouido Island with the northwestern part of the city.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e246079f58819085eaa9c260906880 completed April 17, 2026, 2:39 p.m.
NER Named-entity recognition batch_69f194c7ec148190b01fd215a0c1daa1 completed April 29, 2026, 5:19 a.m.
Created at: April 17, 2026, 4:11 p.m.