Triple

T12038205
Position Surface form Disambiguated ID Type / Status
Subject Vinje E286593 entity
Predicate borderedBy P224 FINISHED
Object Ullensvang E373324 NE FINISHED

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: Ullensvang | Statement: [Vinje, borderedBy, Ullensvang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ullensvang
Context triple: [Vinje, borderedBy, Ullensvang]
  • A. Ullensvang chosen
    Ullensvang is a scenic municipality in Vestland county, Norway, known for its fruit orchards, fjord landscapes, and location along the Hardangerfjord.
  • B. Nissedal
    Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
  • C. Verdal
    Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
  • D. Trysil
    Trysil is a Norwegian municipality renowned for its large alpine ski resort and extensive outdoor recreation opportunities.
  • E. Bjerkreim
    Bjerkreim is a rural municipality in southwestern Norway known for its rivers, salmon fishing, and agricultural landscape.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6ab4669e48190b59246358b0383ab completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9040a8be881908f4841145a7b4e86 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63edddad48190b5b4da184fde27dd completed May 2, 2026, 6:13 p.m.
Created at: April 8, 2026, 9:47 p.m.