Triple

T15506958
Position Surface form Disambiguated ID Type / Status
Subject Taoyuan Airport MRT E379105 entity
Predicate hasStation P35 FINISHED
Object Kengkou Station E859009 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: Kengkou Station | Statement: [Taoyuan Airport MRT, hasStation, Kengkou Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kengkou Station
Context triple: [Taoyuan Airport MRT, hasStation, Kengkou Station]
  • A. Kengkou station chosen
    Kengkou station is a metro station on the Guangzhou Metro network in Guangzhou, China.
  • B. Jiantan Station
    Jiantan Station is a Taipei Metro station in Taiwan that serves as a major access point for visitors to the popular Shilin Night Market.
  • C. Lijiao Station
    Lijiao Station is an interchange station on the Guangzhou Metro system in Guangzhou, China, serving as a local transit hub for passengers in its surrounding urban area.
  • D. Liyuan Station
    Liyuan Station is a stop on Beijing's Batong Line serving the eastern suburbs of the city.
  • E. Jiangtai Station
    Jiangtai Station is a Beijing Subway station that serves as a key access point to the nearby 798 Art Zone and surrounding Chaoyang District areas.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fcea8888190a7b69aca360183c3 completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0067948b308190a434cdf1d45ebef4 completed May 10, 2026, 11:10 a.m.
Created at: April 10, 2026, 3:55 a.m.