Triple

T18113068
Position Surface form Disambiguated ID Type / Status
Subject Nord-Fron E433529 entity
Predicate borderedBy P224 FINISHED
Object Vang 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: Vang | Statement: [Nord-Fron, borderedBy, Vang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vang
Context triple: [Nord-Fron, borderedBy, Vang]
  • A. Vang chosen
    Vang is a rural municipality in Innlandet county, Norway, known for its mountainous landscapes, traditional farming communities, and outdoor recreation opportunities.
  • B. Vang valley
    Vang valley is a scenic valley area in Vang municipality in Innlandet county, Norway, known for its lakes, mountains, and traditional rural landscapes.
  • C. Le Vin
    Le Vin is a section of Charles Baudelaire’s poetry collection Les Fleurs du mal that explores themes of intoxication, escape, and existential despair through the motif of wine.
  • D. Winenne
    Winenne is a small village in the municipality of Houyet in the Wallonia region of southern Belgium.
  • E. Fumel
    Fumel is a small town in southwestern France, known for its location along the Lot River and its historical industrial and agricultural activities.
  • 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_69d8b90916008190a1f110bd7ced5473 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ddd3fd9c81909bfe95927f7553e3 completed April 19, 2026, 1:51 p.m.
Created at: April 10, 2026, 10:28 a.m.