Triple

T12057634
Position Surface form Disambiguated ID Type / Status
Subject Son Kee-chung E287082 entity
Predicate placeOfBirth P1 FINISHED
Object Sinuiju E287083 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: Sinuiju | Statement: [Son Kee-chung, placeOfBirth, Sinuiju]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sinuiju
Context triple: [Son Kee-chung, placeOfBirth, Sinuiju]
  • A. Sinuiju, Korea chosen
    Sinuiju, Korea is a North Korean city on the Yalu River bordering China, known as an important industrial and transportation hub.
  • B. 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.
  • C. 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.
  • D. Nampo
    Nampo is a major port city in southwestern North Korea, known for its industrial facilities and strategic location on the Yellow Sea.
  • E. Nampo-dong
    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.
  • 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_69d6ab4780948190bdb9f7620c2ac27e completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9043bf0ec8190a51ef2641808320c completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a64c8bc8190920c1ed858ea4794 completed May 2, 2026, 2:29 p.m.
Created at: April 8, 2026, 9:47 p.m.