Triple

T1032668
Position Surface form Disambiguated ID Type / Status
Subject Korean People's Army E22286 entity
Predicate headquartersLocation P62 FINISHED
Object Pyongyang E24920 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: Pyongyang | Statement: [Korean People's Army, headquartersLocation, Pyongyang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pyongyang
Context triple: [Korean People's Army, headquartersLocation, Pyongyang]
  • A. Pyongyang chosen
    Pyongyang is the capital and largest city of North Korea, serving as its political, economic, and cultural center.
  • B. Seoul
    Seoul is the capital and largest metropolis of South Korea, known as a major global center for technology, culture, and finance.
  • C. 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.
  • D. Neryungri
    Neryungri is a major coal-mining and industrial city in southeastern Siberia, Russia, known as one of the key urban centers of the Sakha Republic (Yakutia).
  • 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_69a493d848848190aed4011b34b2e8d3 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b811916481908c05c2dd5ec802ec completed March 1, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c15bb8481909ba68f5807581b18 completed March 7, 2026, 4:02 p.m.
Created at: March 1, 2026, 7:41 p.m.