Triple

T8241579
Position Surface form Disambiguated ID Type / Status
Subject City Hall Station (Busan Metro) E192547 entity
Predicate serves P98 FINISHED
Object Busan City Hall E191335 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 City Hall | Statement: [City Hall Station (Busan Metro), serves, Busan City Hall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Busan City Hall
Context triple: [City Hall Station (Busan Metro), serves, Busan City Hall]
  • A. Busan Metropolitan City Hall chosen
    Busan Metropolitan City Hall is the main administrative headquarters of the Busan metropolitan government in South Korea.
  • B. Ulsan City Hall
    Ulsan City Hall is the main municipal government building and administrative center serving the city of Ulsan, South Korea.
  • C. Incheon City Hall
    Incheon City Hall is the main administrative and governmental headquarters of the metropolitan city of Incheon, South Korea.
  • D. Gwangju City Hall
    Gwangju City Hall is the main municipal government building and administrative center of Gwangju, a major city in South Korea.
  • E. Daejeon City Hall
    Daejeon City Hall is the main municipal government complex of Daejeon, South Korea, housing the city’s administrative offices and executive leadership.
  • 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_69ca82dc8f148190a2c75a98501a7b91 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb783f67708190a4e1c4078c3a6fb0 completed March 31, 2026, 7:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd351871ac81909f8e4a72a6b99ac3 completed April 1, 2026, 3:09 p.m.
Created at: March 30, 2026, 5:47 p.m.