Triple

T15690361
Position Surface form Disambiguated ID Type / Status
Subject Bømlo Municipality E380311 entity
Predicate hasIsland P970 FINISHED
Object Espevær E380400 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: Espevær | Statement: [Bømlo Municipality, hasIsland, Espevær]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Espevær
Context triple: [Bømlo Municipality, hasIsland, Espevær]
  • A. Espevær chosen
    Espevær is a small island and fishing village in Vestland county, Norway, known for its traditional coastal culture and scenic maritime environment.
  • B. Tovere
    Tovere is a small locality or hamlet that forms part of the municipality of Moltrasio in northern Italy’s Lake Como area.
  • C. Tysvær
    Tysvær is a coastal municipality in southwestern Norway known for its fjords, islands, and location between the cities of Haugesund and Stavanger.
  • D. Storvreten
    Storvreten is a residential locality within Botkyrka Municipality in the Stockholm County area of Sweden.
  • E. Skreia
    Skreia is a village in Østre Toten Municipality in Innlandet county, Norway, known for its rural setting near Lake Mjøsa.
  • 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_69d86d99e860819094b6957cde470f2c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f4e59988190aaf12f6a07c8f0e4 completed April 16, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6eebaccc8190a61fb2f9b9bdbcc1 completed May 9, 2026, 5:29 p.m.
Created at: April 10, 2026, 4:44 a.m.