Triple

T23407686
Position Surface form Disambiguated ID Type / Status
Subject Alpensia Ski Jumping Centre E559979 entity
Predicate city P40 FINISHED
Object Pyeongchang-gun 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-gun | Statement: [Alpensia Ski Jumping Centre, city, Pyeongchang-gun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pyeongchang-gun
Context triple: [Alpensia Ski Jumping Centre, city, Pyeongchang-gun]
  • A. Pyeongchang County chosen
    Pyeongchang County is a mountainous region in South Korea best known internationally for hosting the 2018 Winter Olympics.
  • B. Pyeongchang-eup
    Pyeongchang-eup is the main urban township and administrative center of Pyeongchang County in Gangwon Province, South Korea.
  • C. Jeungpyeong-gun
    Jeungpyeong-gun is a rural county in central South Korea known for its agricultural landscape and location within North Chungcheong Province.
  • D. Boeun-gun
    Boeun-gun is a rural county in central South Korea known for its apple orchards, scenic mountains, and historic Beopjusa Temple in Songnisan National Park.
  • E. Hwacheon County
    Hwacheon County is a rural county in Gangwon Province, South Korea, known for its mountainous terrain, lakes, and popular ice fishing festival.
  • 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_69e2454b3a5881909c64773dc8a5d289 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1a50f3f90819084fb682597fee1e1 completed April 29, 2026, 6:28 a.m.
Created at: April 17, 2026, 5:38 p.m.