Triple

T8094448
Position Surface form Disambiguated ID Type / Status
Subject Sauda E188946 entity
Predicate hasNeighbouringMunicipality 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: [Sauda, hasNeighbouringMunicipality, Ullensvang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ullensvang
Context triple: [Sauda, hasNeighbouringMunicipality, 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_69ca82b7b3e88190b9041ab0ef28b3cb completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb429089cc81909e4625f9cc7e305f completed March 31, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc65afac4819094282e7d63619111 completed April 2, 2026, 1:28 a.m.
Created at: March 30, 2026, 5:30 p.m.