Triple

T1361016
Position Surface form Disambiguated ID Type / Status
Subject Busan National University of Education E29098 entity
Predicate locatedInAdministrativeTerritory P40 FINISHED
Object Busan Metropolitan City E4279 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 Metropolitan City | Statement: [Busan National University of Education, locatedInAdministrativeTerritory, Busan Metropolitan City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Busan Metropolitan City
Context triple: [Busan National University of Education, locatedInAdministrativeTerritory, Busan Metropolitan City]
  • A. Incheon
    Incheon is a major port city in northwestern South Korea, known for its international airport and role as a key transportation and economic hub.
  • B. Ulsan
    Ulsan is a major industrial city in southeastern South Korea, known for its large automobile, shipbuilding, and petrochemical complexes.
  • C. Busan chosen
    Busan is South Korea’s second-largest city and a major international port known for its bustling harbor, beaches, and coastal scenery.
  • D. Daegu
    Daegu is a major metropolitan city in southeastern South Korea known for its textile industry, electronics manufacturing, and cultural festivals.
  • E. Daejeon
    Daejeon is a major city in central South Korea known as a hub for science, technology, and research institutions.
  • 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_69a498d77abc8190913bf57e5f51d2c4 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c2b156b081909c99ada70a969fc0 completed March 1, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69afaf0adcd88190a2627ae97157884e completed March 10, 2026, 5:41 a.m.
Created at: March 1, 2026, 7:56 p.m.