Triple

T22780310
Position Surface form Disambiguated ID Type / Status
Subject Alpensia Cross-Country Centre E563818 entity
Predicate locatedIn P40 FINISHED
Object Pyeongchang 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: Pyeongchang | Statement: [Alpensia Cross-Country Centre, locatedIn, Pyeongchang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pyeongchang
Context triple: [Alpensia Cross-Country Centre, locatedIn, Pyeongchang]
  • A. Pyeongchang chosen
    Pyeongchang is a county in South Korea best known internationally for hosting the 2018 Winter Olympics.
  • B. Gangneung Oval
    Gangneung Oval is a purpose-built long-track speed skating venue in Gangneung, South Korea, used for major international competitions including the 2018 Winter Olympics.
  • C. 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.
  • D. Pyeongchang-eup
    Pyeongchang-eup is the main urban township and administrative center of Pyeongchang County in Gangwon Province, South Korea.
  • E. 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.
  • 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_69e2455500788190b4b33030461f3bbd completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17c2cab0881908df1d0629b43d350 completed April 29, 2026, 3:34 a.m.
Created at: April 17, 2026, 3:28 p.m.