Triple

T9084565
Position Surface form Disambiguated ID Type / Status
Subject Bujeon Station area E217717 entity
Predicate servedBy P82 FINISHED
Object Bujeon Station E776481 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: Bujeon Station | Statement: [Bujeon Station area, servedBy, Bujeon Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bujeon Station
Context triple: [Bujeon Station area, servedBy, Bujeon Station]
  • A. Bujeon Station chosen
    Bujeon Station is a railway station in Busan, South Korea, serving as a local transportation hub with connections to regional and urban rail services.
  • B. Bupyeong station
    Bupyeong station is a major transit hub in Incheon, South Korea, serving both the Incheon Subway and Seoul Metropolitan Subway Line 1 and connecting to nearby commercial and residential areas.
  • C. Myeongnyun Station
    Myeongnyun Station is a metro station in Busan, South Korea, serving the Dongnae District on the Busan Metro network.
  • D. Jinju Station
    Jinju Station is a railway station in Jinju, South Korea, serving as a regional transportation hub connecting the city to other parts of the country.
  • E. Gyeyang Station
    Gyeyang Station is a major transit hub in Incheon, South Korea, serving as an interchange between the Incheon Subway, AREX airport railroad, and local bus routes.
  • 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_69ca83d7a0388190ba1af89ed7ba36f9 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc960b45fc8190adf4bdc41b103e86 completed April 1, 2026, 3:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69d017c893fc819087d18db2383b9bb4 completed April 3, 2026, 7:40 p.m.
Created at: March 30, 2026, 7:13 p.m.