Triple

T15529031
Position Surface form Disambiguated ID Type / Status
Subject Strand E370161 entity
Predicate locatedInDistrict P40 FINISHED
Object Ryfylke E329313 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: Ryfylke | Statement: [Strand, locatedInDistrict, Ryfylke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ryfylke
Context triple: [Strand, locatedInDistrict, Ryfylke]
  • A. Ryfylke chosen
    Ryfylke is a traditional district in southwestern Norway known for its fjords, islands, and mountainous coastal landscape in Rogaland county.
  • B. Fjordane
    Fjordane is a traditional district in western Norway known for its dramatic fjord landscapes and coastal scenery.
  • C. Romsdal
    Romsdal is a traditional district in Møre og Romsdal county in western Norway, known for its dramatic fjords, mountains, and the town of Molde.
  • D. Nordmøre
    Nordmøre is a traditional district in the northern part of Møre og Romsdal county in western Norway, known for its coastal landscapes, fjords, and fishing communities.
  • E. Nordhordland
    Nordhordland is a traditional district in western Norway known for its coastal landscapes, fjords, and proximity to the city of Bergen.
  • 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e0414620588190958ffde651ccab5f completed April 16, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a008a1f8d648190b9c6280b875a17e4 completed May 10, 2026, 1:37 p.m.
Created at: April 10, 2026, 4:05 a.m.