Triple

T16852684
Position Surface form Disambiguated ID Type / Status
Subject LG Twin Towers E409711 entity
Predicate transportAccess P1288 FINISHED
Object Yeouido Station E412865 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 Station | Statement: [LG Twin Towers, transportAccess, Yeouido Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yeouido Station
Context triple: [LG Twin Towers, transportAccess, Yeouido Station]
  • A. Yeouido Station chosen
    Yeouido Station is a major Seoul Metropolitan Subway station on Yeouido Island that serves as a key transit hub for the city’s financial and business district.
  • B. Yeongdeungpo Station
    Yeongdeungpo Station is a major railway and subway interchange in Seoul, South Korea, serving as an important transportation and commercial hub for the Yeongdeungpo area.
  • C. Seocho Station
    Seocho Station is a subway station in southern Seoul, South Korea, serving as a transit hub for commuters in the Seocho area.
  • D. Gwanak Station
    Gwanak Station is a railway station in South Korea that serves the city of Anyang and connects it to the broader Seoul metropolitan rail network.
  • E. Yongsan station
    Yongsan station is a major railway and subway hub in central Seoul, South Korea, serving high-speed, intercity, and commuter trains as well as multiple metro lines.
  • 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_6a00c2a6f2c48190874839f78f943fdb completed May 10, 2026, 5:38 p.m.
Created at: April 10, 2026, 5:24 a.m.