Triple

T23218611
Position Surface form Disambiguated ID Type / Status
Subject Gangneung Station E580819 entity
Predicate servedCity P3936 FINISHED
Object Gangneung 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: Gangneung | Statement: [Gangneung Station, servedCity, Gangneung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gangneung
Context triple: [Gangneung Station, servedCity, Gangneung]
  • A. Gangneung chosen
    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. Pyeongtaek
    Pyeongtaek is a South Korean city in Gyeonggi Province known for its major U.S. and UN military presence, including large bases such as Camp Humphreys.
  • C. Jeongeup
    Jeongeup is a city in South Korea known for its location in North Jeolla Province and its cultural and historical heritage.
  • D. Wonju
    Wonju is a city in South Korea’s Gangwon Province known historically as a strategic military site and today as a regional commercial and transportation hub.
  • E. Pohang
    Pohang is a major industrial and port city in South Korea, best known as the home of the global steelmaker POSCO and a key hub on the country’s east coast.
  • 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_69e2460389408190be74f41d217799a9 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f191675de48190858907872a065c56 completed April 29, 2026, 5:04 a.m.
Created at: April 17, 2026, 4:08 p.m.