Triple

T15529045
Position Surface form Disambiguated ID Type / Status
Subject Strand E370161 entity
Predicate hasFjord P56784 FINISHED
Object Idsefjorden 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: Idsefjorden | Statement: [Strand, hasFjord, Idsefjorden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Idsefjorden
Context triple: [Strand, hasFjord, Idsefjorden]
  • A. Esefjorden chosen
    Esefjorden is a scenic fjord in western Norway known for its dramatic mountain landscapes and picturesque waterfront views.
  • B. Langfjorden
    Langfjorden is a notable fjord in Norway’s Møre og Romsdal county, characterized by its deep waters and steep surrounding mountains.
  • C. Isefjord
    Isefjord is a large, shallow fjord and coastal inlet on the island of Zealand in Denmark, known for its varied birdlife, recreational boating, and surrounding seaside towns.
  • D. Vadheimsfjorden
    Vadheimsfjorden is a narrow Norwegian fjord known for its steep surrounding mountains and scenic coastal landscape.
  • E. Beisfjorden
    Beisfjorden is a fjord in Nordland county, Norway, known as an inner branch of the larger Ofotfjord near the town of Narvik.
  • 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e0414620588190958ffde651ccab5f completed April 16, 2026, 1:54 a.m.
Created at: April 10, 2026, 4:05 a.m.