Triple

T15690381
Position Surface form Disambiguated ID Type / Status
Subject Bømlo Municipality E380311 entity
Predicate hasSettlement P1068 FINISHED
Object Finnås E389214 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: Finnås | Statement: [Bømlo Municipality, hasSettlement, Finnås]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Finnås
Context triple: [Bømlo Municipality, hasSettlement, Finnås]
  • A. Finnås chosen
    Finnås is a village and former church-centered parish on the island municipality of Bømlo in Vestland county, Norway.
  • B. Fagernes
    Fagernes is a small town in central Norway that serves as a regional hub and gateway to the mountainous Valdres district.
  • C. Gröndal
    Gröndal is a residential district in southern Stockholm, Sweden, known for its waterfront location on Lake Mälaren and mix of early 20th-century and modern architecture.
  • D. Fyresdal
    Fyresdal is a rural municipality in Telemark county, Norway, known for its forests, lakes, and traditional farming communities.
  • E. Brårud
    Brårud is a small village located within the municipality of Nes in Akershus county, Norway.
  • 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_6a014134601c81909f7f4a95d558e067 completed May 11, 2026, 2:38 a.m.
Created at: April 10, 2026, 4:44 a.m.