Triple

T22312725
Position Surface form Disambiguated ID Type / Status
Subject 1999 Asian Winter Games E551561 entity
Predicate hostCity P1798 FINISHED
Object Yongpyong 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: Yongpyong | Statement: [1999 Asian Winter Games, hostCity, Yongpyong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yongpyong
Context triple: [1999 Asian Winter Games, hostCity, Yongpyong]
  • A. Gangneung
    Gangneung is a coastal city in South Korea’s Gangwon Province, known for its beaches, cultural festivals, and role as a host city during the 2018 Pyeongchang Winter Olympics.
  • B. Pyonggang
    Pyonggang is a town in North Korea’s Kangwon Province that was a strategically important site during the Korean War.
  • C. Jonggol
    Jonggol is a rapidly developing district in West Java, Indonesia, known for its rural landscapes, growing residential areas, and proximity to the Jakarta metropolitan region.
  • D. Jeongseon chosen
    Jeongseon is a mountainous county in Gangwon Province, South Korea, known for its winter sports facilities and role as a competition venue during the 2018 Winter Olympics.
  • E. Taebong
    Taebong was a short-lived Korean kingdom of the early 10th century that emerged during the Later Three Kingdoms period before being absorbed by Goryeo.
  • 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_69e11e4776588190abb21e5cea79973f completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15750f76c81909d6f788928f503f1 completed April 29, 2026, 12:56 a.m.
Created at: April 16, 2026, 8:42 p.m.