Triple

T1557763
Position Surface form Disambiguated ID Type / Status
Subject Suyeong District E33247 entity
Predicate hasTransport P1298 FINISHED
Object Busan Metro Line 3 E36979 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 Metro Line 3 | Statement: [Suyeong District, hasTransport, Busan Metro Line 3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Busan Metro Line 3
Context triple: [Suyeong District, hasTransport, Busan Metro Line 3]
  • A. Busan Metro chosen
    Busan Metro is the rapid transit system serving the city of Busan, South Korea, providing extensive urban and suburban rail transportation across the metropolitan area.
  • B. Gwangju Metro
    Gwangju Metro is the urban rapid transit system serving the city of Gwangju in South Korea.
  • C. Daegu Metro
    Daegu Metro is the urban rapid transit system serving the city of Daegu in South Korea, providing high-capacity rail transportation across the metropolitan area.
  • D. Daejeon Metro
    Daejeon Metro is the urban rapid transit system serving the city of Daejeon in South Korea.
  • E. Incheon Subway
    Incheon Subway is the urban rapid transit system serving the city of Incheon, South Korea, connecting major districts and linking with the Seoul Metropolitan 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_69a885ef9cf48190b0af0f5ce3d02231 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9088355048190adad5ea2bb558d13 completed March 5, 2026, 4:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad401e12088190b6f0f5b0d8a423cf completed March 8, 2026, 9:23 a.m.
Created at: March 4, 2026, 7:27 p.m.