Triple

T6836085
Position Surface form Disambiguated ID Type / Status
Subject Nampo Station E157453 entity
Predicate locatedIn P40 FINISHED
Object Nampo-dong E605668 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: Nampo-dong | Statement: [Nampo Station, locatedIn, Nampo-dong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nampo-dong
Context triple: [Nampo Station, locatedIn, Nampo-dong]
  • A. Nampo-dong chosen
    Nampo-dong is a bustling commercial and shopping district in central Busan, South Korea, known for its markets, street food, and proximity to the city’s harbor.
  • B. Nopo-dong
    Nopo-dong is a neighborhood in Busan, South Korea, known as a major transportation hub and gateway to the city.
  • C. Mansudae district
    Mansudae district is a central area of Pyongyang, North Korea, known for its major political monuments, cultural institutions, and prominent artistic facilities.
  • D. Taedonggang District
    Taedonggang District is an administrative district of Pyongyang, North Korea, known for hosting major political monuments and government-related sites.
  • E. Pyongchon District
    Pyongchon District is a central urban district of Pyongyang, North Korea, known for its industrial facilities and major national 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_69c6882c53608190b99aebef079b23bd completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d67c1c508190ab39b8aaaaacc628 completed March 27, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c75115c74c81909b02e4c49a98663c completed March 28, 2026, 3:55 a.m.
Created at: March 27, 2026, 2:19 p.m.