Triple

T8094458
Position Surface form Disambiguated ID Type / Status
Subject Sauda E188946 entity
Predicate hasFjord P56784 FINISHED
Object Saudafjorden E736432 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: Saudafjorden | Statement: [Sauda, hasFjord, Saudafjorden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saudafjorden
Context triple: [Sauda, hasFjord, Saudafjorden]
  • A. Saudafjorden chosen
    Saudafjorden is a narrow, scenic fjord in Rogaland county, southwestern Norway, known for its steep mountainsides and industrial town of Sauda at its inner end.
  • B. Storfjorden
    Storfjorden is a major fjord in western Norway known for its dramatic landscapes and proximity to the coastal town of Ålesund.
  • C. Sandviksfjorden
    Sandviksfjorden is a celebrated 19th-century Norwegian landscape painting by Hans Gude, depicting a coastal fjord scene with detailed maritime and atmospheric effects.
  • D. Beisfjorden
    Beisfjorden is a fjord in Nordland county, Norway, known as an inner branch of the larger Ofotfjord near the town of Narvik.
  • E. 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.
  • 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_69ca82b7b3e88190b9041ab0ef28b3cb completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb429089cc81909e4625f9cc7e305f completed March 31, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce4d5b80b48190909ca7775fda2ed9 completed April 2, 2026, 11:04 a.m.
Created at: March 30, 2026, 5:30 p.m.