Triple

T6686586
Position Surface form Disambiguated ID Type / Status
Subject Daegu Gwangyeoksi E152111 entity
Predicate historicalName P65 FINISHED
Object Daegu-bu E27919 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: Daegu-bu | Statement: [Daegu Gwangyeoksi, historicalName, Daegu-bu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daegu-bu
Context triple: [Daegu Gwangyeoksi, historicalName, Daegu-bu]
  • A. Daegu chosen
    Daegu is a major metropolitan city in southeastern South Korea known for its textile industry, electronics manufacturing, and cultural festivals.
  • B. Uijeongbu
    Uijeongbu is a city in South Korea known as a suburban hub north of Seoul, featuring residential districts, commercial centers, and a history of hosting U.S. military bases.
  • C. Pohang
    Pohang is a major industrial and port city in South Korea, best known as the home of the global steelmaker POSCO and a key hub on the country’s east coast.
  • D. Dongducheon
    Dongducheon is a city in northern South Korea known for its proximity to the Demilitarized Zone and the presence of U.S. military bases.
  • E. Gwangju
    Gwangju is a major metropolitan city in southwestern South Korea known for its rich cultural heritage and pivotal role in the country’s pro-democracy movement.
  • 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_69c687f9977c819097e7f5ada4fe522e completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b14cd6748190aad4badd5f253478 completed March 27, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7a30754cc8190beeb97b48c167a15 completed March 28, 2026, 9:44 a.m.
Created at: March 27, 2026, 2:04 p.m.