Triple

T14002017
Position Surface form Disambiguated ID Type / Status
Subject Boknafjorden E336848 entity
Predicate hasInflow P967 FINISHED
Object Skjoldafjorden E1159443 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: Skjoldafjorden | Statement: [Boknafjorden, hasInflow, Skjoldafjorden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skjoldafjorden
Context triple: [Boknafjorden, hasInflow, Skjoldafjorden]
  • A. Skudenesfjorden
    Skudenesfjorden is a fjord in Rogaland county, southwestern Norway, lying along the coast by the island municipality of Karmøy and opening into the North Sea.
  • B. Storfjorden
    Storfjorden is a major fjord in western Norway known for its dramatic landscapes and proximity to the coastal town of Ålesund.
  • C. Vindafjorden chosen
    Vindafjorden is a fjord in Rogaland county, Norway, known as one of the main inner branches of the larger Boknafjorden system.
  • D. Bjørnafjorden
    Bjørnafjorden is a large fjord in western Norway known for its scenic coastal landscape and role as an important marine and transport corridor in Vestland county.
  • E. Kirkefjorden
    Kirkefjorden is a scenic fjord on the island of Moskenesøya in Norway’s Lofoten archipelago, known for its steep mountainsides and dramatic coastal landscape.
  • 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ed06a50819093ddc64f55050689 completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d379bc881908b7954c633787165 completed May 9, 2026, 1:57 p.m.
Created at: April 9, 2026, 10:19 p.m.