Triple

T9928486
Position Surface form Disambiguated ID Type / Status
Subject Dong-gu, Busan E192582 entity
Predicate contains P35 FINISHED
Object Busan Station E36550 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: Busan Station | Statement: [Dong-gu, Busan, contains, Busan Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Busan Station
Context triple: [Dong-gu, Busan, contains, Busan Station]
  • A. Busan Station chosen
    Busan Station is a major railway hub in Busan, South Korea, serving high-speed KTX trains and regional services as one of the country’s key transportation centers.
  • B. Pohang Station
    Pohang Station is a major railway station in Pohang, South Korea, serving as the eastern endpoint of high-speed KTX services and a key regional transportation hub.
  • C. Daegu Station
    Daegu Station is a major railway and metro hub in Daegu, South Korea, serving as a key transit point for regional and urban transportation.
  • D. Gwangju station
    Gwangju station is a major railway station in Gwangju, South Korea, serving as a key hub for regional and intercity train services.
  • E. Incheon Station
    Incheon Station is a major railway and subway terminus in the city of Incheon, South Korea, serving as an important transportation hub in the greater Seoul metropolitan area.
  • 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_69ca82dd978c8190947124ab0d3315ac completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb59d7ad08190982a1584547190bd completed April 2, 2026, 12:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20e1eace88190a591cbab02153869 completed April 5, 2026, 7:24 a.m.
Created at: March 30, 2026, 8:43 p.m.