Triple

T16852648
Position Surface form Disambiguated ID Type / Status
Subject LG Twin Towers E409711 entity
Predicate location P40 FINISHED
Object Yeouido-dong E90260 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: Yeouido-dong | Statement: [LG Twin Towers, location, Yeouido-dong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yeouido-dong
Context triple: [LG Twin Towers, location, Yeouido-dong]
  • A. Yeouido-dong chosen
    Yeouido-dong is a major financial and business district in Seoul, South Korea, known for its skyscrapers, corporate headquarters, and role as a political and economic hub.
  • B. Yangjeong-dong
    Yangjeong-dong is a neighborhood (dong) located within Busanjin District in the city of Busan, South Korea.
  • C. Cheongun-dong
    Cheongun-dong is a neighborhood in central Seoul, South Korea, known for its proximity to historic sites such as Gyeongbokgung Palace and the Blue House.
  • D. Cheongnyong-dong
    Cheongnyong-dong is a neighborhood located within Geumjeong District in Busan, South Korea.
  • E. Seocho-dong
    Seocho-dong is a neighborhood in southern Seoul, South Korea, known for its affluent residential areas, major cultural venues, and proximity to key business districts.
  • 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_69d88395e6c88190b22730f335107c14 completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b37abadc81909d02d329403497d6 completed April 18, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7a08be48190bd2dbf83205c83ad completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:24 a.m.