Triple

T15360780
Position Surface form Disambiguated ID Type / Status
Subject Norwegian County Road 63 E367282 entity
Predicate passesThrough P225 FINISHED
Object Geiranger E370860 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: Geiranger | Statement: [Norwegian County Road 63, passesThrough, Geiranger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Geiranger
Context triple: [Norwegian County Road 63, passesThrough, Geiranger]
  • A. Geiranger chosen
    Geiranger is a small Norwegian village in the Sunnmøre region of Møre og Romsdal, renowned as a popular tourist destination surrounded by dramatic fjord and mountain scenery.
  • B. Geirangerfjord
    Geirangerfjord is a famous UNESCO-listed fjord in western Norway renowned for its steep cliffs, dramatic waterfalls, and stunning natural scenery.
  • C. Nærøy
    Nærøy is a former coastal municipality in Trøndelag county, Norway, known for its fishing communities and island-dotted landscape.
  • D. Nærøyfjord
    Nærøyfjord is a narrow, dramatic branch of Norway’s Sognefjord and a UNESCO World Heritage Site renowned for its steep mountainsides, waterfalls, and picturesque fjord landscapes.
  • E. Flåm
    Flåm is a small Norwegian village in Aurland municipality, best known for its dramatic fjord scenery and the scenic Flåm Railway that attracts many tourists.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e4607408190ab281a7f7a8012d3 completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a001f7d79348190aba1889a7eb3d7c8 completed May 10, 2026, 6:02 a.m.
Created at: April 10, 2026, 3:18 a.m.