Triple

T15844932
Position Surface form Disambiguated ID Type / Status
Subject Bodø Harbour E384190 entity
Predicate locatedIn P40 FINISHED
Object Bodø NE NERFINISHED

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: Bodø | Statement: [Bodø Harbour, locatedIn, Bodø]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bodø
Context triple: [Bodø Harbour, locatedIn, Bodø]
  • A. Bodø chosen
    Bodø is a coastal city in northern Norway known as a regional hub for culture, transport, and access to Arctic nature.
  • B. Tromsø
    Tromsø is a city in northern Norway known for its Arctic location, vibrant cultural scene, and prominence as a viewing spot for the Northern Lights.
  • C. Alsvåg
    Alsvåg is a small coastal village in Nordland county, Norway, known for its fishing industry and scenic location within the municipality of Øksnes.
  • D. Porsgrunn
    Porsgrunn is an industrial and port city in Telemark county in southeastern Norway, known for its porcelain production and location along the Telemark Canal.
  • E. Melbu
    Melbu is a small coastal village and fishing community in Hadsel Municipality in Nordland county, Norway.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d86da422088190aac39e32e6c68429 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e142eb20088190bb45e37ce3291ef2 completed April 16, 2026, 8:13 p.m.
Created at: April 10, 2026, 4:50 a.m.