Triple

T3145037
Position Surface form Disambiguated ID Type / Status
Subject Innlandet E65742 entity
Predicate hasBorderWith P224 FINISHED
Object Vestland E75761 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: Vestland | Statement: [Innlandet, hasBorderWith, Vestland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vestland
Context triple: [Innlandet, hasBorderWith, Vestland]
  • A. Vestland chosen
    Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
  • B. Fosen
    Fosen is a peninsula and traditional district in central Norway known for its coastal landscape, wind farms, and location across the Trondheimsfjord from the city of Trondheim.
  • C. Mykland
    Mykland is a small village in Agder county, Norway, known for its rural setting and surrounding forests and lakes.
  • D. Svalbard
    Svalbard is a remote Arctic archipelago known for its rugged glaciers, polar bear habitat, and role as a center for polar research and environmental monitoring.
  • E. Nordland
    Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic landscapes.
  • 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_69ad8582f564819088c27e1f96153938 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada595d4548190b720a6131817833b completed March 8, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b224ed4d748190a2af68bf284110e8 completed March 12, 2026, 2:29 a.m.
Created at: March 8, 2026, 3:05 p.m.