Triple

T15889697
Position Surface form Disambiguated ID Type / Status
Subject Harstad harbour E385283 entity
Predicate locatedOnBodyOfWater P212 FINISHED
Object Vågsfjorden 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: Vågsfjorden | Statement: [Harstad harbour, locatedOnBodyOfWater, Vågsfjorden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vågsfjorden
Context triple: [Harstad harbour, locatedOnBodyOfWater, Vågsfjorden]
  • A. Vågsfjorden chosen
    Vågsfjorden is a fjord in northern Norway known for its scenic coastal landscapes and as a maritime hub for surrounding towns and islands.
  • B. Vadheimsfjorden
    Vadheimsfjorden is a narrow Norwegian fjord known for its steep surrounding mountains and scenic coastal landscape.
  • C. Voldafjorden
    Voldafjorden is a fjord in western Norway known for its steep surrounding mountains and proximity to the town of Volda in Møre og Romsdal county.
  • D. Kvæfjorden
    Kvæfjorden is a fjord in Troms county in northern Norway, known for its scenic coastal landscape and surrounding mountainous terrain.
  • E. Langfjorden
    Langfjorden is a notable fjord in Norway’s Møre og Romsdal county, characterized by its deep waters and steep surrounding mountains.
  • 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_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1561d5c28819094c3541d917a4433 completed April 16, 2026, 9:35 p.m.
Created at: April 10, 2026, 4:51 a.m.