Triple

T23314408
Position Surface form Disambiguated ID Type / Status
Subject Korean Writers’ Union E590664 entity
Predicate location P40 FINISHED
Object Pyongyang NE NERFINISHED

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: Pyongyang | Statement: [Korean Writers’ Union, location, Pyongyang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pyongyang
Context triple: [Korean Writers’ Union, location, Pyongyang]
  • A. Pyongyang chosen
    Pyongyang is the capital and largest city of North Korea, serving as its political, economic, and cultural center.
  • B. Pyeongyang
    Pyeongyang is the historic city that became the capital of the ancient Korean kingdom of Goguryeo and is now the capital of North Korea.
  • C. Sinuiju, Korea
    Sinuiju, Korea is a North Korean city on the Yalu River bordering China, known as an important industrial and transportation hub.
  • D. Wonsan
    Wonsan is a port city on North Korea’s east coast, known for its strategic military importance and role as a regional transportation and industrial hub.
  • E. Kim Chaek City
    Kim Chaek City is an industrial port city in North Hamgyong Province, North Korea, named in honor of the Korean War general and politician Kim Chaek.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e25d1d32188190948eb76909d1dcc3 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1977ee5d08190a9519d7867d6bef9 completed April 29, 2026, 5:30 a.m.
Created at: April 17, 2026, 5:06 p.m.