Triple

T14371933
Position Surface form Disambiguated ID Type / Status
Subject South Gyeongsang Province E356377 entity
Predicate containsCity P294 FINISHED
Object Yangsan E159717 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: Yangsan | Statement: [South Gyeongsang Province, containsCity, Yangsan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yangsan
Context triple: [South Gyeongsang Province, containsCity, Yangsan]
  • A. Yangsan chosen
    Yangsan is a city in South Gyeongsang Province, South Korea, known as a growing residential and educational hub near Busan.
  • B. Yuchang
    Yuchang is a Chinese actor and singer best known for his roles in popular youth and coming-of-age films and television dramas.
  • C. Jinshan
    Jinshan is a suburban district in the southwest of Shanghai, China, known for its coastal location, industrial zones, and residential communities.
  • D. Yangcheng
    Yangcheng was an ancient Chinese city traditionally regarded as one of the earliest capitals of the Xia dynasty.
  • E. Jinyang
    Jinyang is the historical name of the city now known as Taiyuan, a major urban and industrial center in northern China’s Shanxi province.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8fb2082c8190b42cc5f2bab4f574 completed April 14, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c5363a081909681b54c1d8218dc completed May 8, 2026, 2:37 a.m.
Created at: April 10, 2026, 1:15 a.m.