Triple

T7629558
Position Surface form Disambiguated ID Type / Status
Subject Geumjeongsan E172724 entity
Predicate hasAccessPoint P1985 FINISHED
Object Oncheonjang Station E220100 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: Oncheonjang Station | Statement: [Geumjeongsan, hasAccessPoint, Oncheonjang Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oncheonjang Station
Context triple: [Geumjeongsan, hasAccessPoint, Oncheonjang Station]
  • A. Oncheonjang Station chosen
    Oncheonjang Station is a subway station in Busan, South Korea, serving the Oncheonjang area in Dongnae District and providing access to its hot spring and commercial zones.
  • B. Seodaejeon Station
    Seodaejeon Station is a major railway station in Daejeon, South Korea, serving as an important stop on national rail lines including high-speed services.
  • C. Myeongnyun Station
    Myeongnyun Station is a metro station in Busan, South Korea, serving the Dongnae District on the Busan Metro network.
  • D. Dongnae Station
    Dongnae Station is a major subway station in Busan, South Korea, serving as an important transit hub within the city's metro network.
  • E. Yeonsu Station
    Yeonsu Station is a subway station in Incheon, South Korea, serving the Yeonsu District on the Incheon Subway Line 1.
  • 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_69c699517e348190bd3348b6889200f2 completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c6fa84adb08190885138fc9b908ebf completed March 27, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8ac8d59048190948eebf6f5979cf9 completed March 29, 2026, 4:37 a.m.
Created at: March 27, 2026, 3:56 p.m.