Triple

T15345284
Position Surface form Disambiguated ID Type / Status
Subject Norheimsund E366899 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Ålvik E1180810 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: Ålvik | Statement: [Norheimsund, hasNearbySettlement, Ålvik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ålvik
Context triple: [Norheimsund, hasNearbySettlement, Ålvik]
  • A. Ålvik chosen
    Ålvik is a small industrial village in Kvam municipality in Vestland county, western Norway, known historically for its ferroalloy production and scenic fjordside setting.
  • B. Alvdal
    Alvdal is a rural municipality in Innlandet county, Norway, known for its agricultural landscape, outdoor recreation, and association with the author Kjell Aukrust.
  • C. Håvik
    Håvik is a small coastal village located in Karmøy municipality in Rogaland county, southwestern Norway.
  • D. Tingvoll
    Tingvoll is a small municipality and village area in western Norway known for its rural landscape, fjords, and agricultural traditions.
  • E. Åkrehamn
    Åkrehamn is a coastal town in southwestern Norway known for its fishing industry and scenic North Sea shoreline.
  • 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e163a3c8190ab933411372c1573 completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffbe60d4a08190833397c75b56932c completed May 9, 2026, 11:08 p.m.
Created at: April 10, 2026, 3:17 a.m.