Triple

T8177252
Position Surface form Disambiguated ID Type / Status
Subject SRT (via some services to Busan area) E190967 entity
Predicate primaryTerminus P388 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: [SRT (via some services to Busan area), primaryTerminus, Busan station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Busan station
Context triple: [SRT (via some services to Busan area), primaryTerminus, 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. Gwangju station
    Gwangju station is a major railway station in Gwangju, South Korea, serving as a key hub for regional and intercity train services.
  • 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. Dongdaegu Station
    Dongdaegu Station is a major railway and transportation hub in Daegu, South Korea, serving high-speed KTX trains, conventional rail, and the city’s metro network.
  • E. Yeonsan Station
    Yeonsan Station is a major transit hub in Busan, South Korea, serving as an important interchange point on the city’s subway network.
  • 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_69ca82c1c0a08190bf8692b4d91a03ca completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4aba0dd88190828080d0d89612eb completed March 31, 2026, 4:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69cced64c9588190b8db6452c364347d completed April 1, 2026, 10:03 a.m.
Created at: March 30, 2026, 5:40 p.m.