Triple

T14028583
Position Surface form Disambiguated ID Type / Status
Subject Sør-Fron E337527 entity
Predicate hasGeographicalFeature P1094 FINISHED
Object Gudbrandsdalen valley E105262 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: Gudbrandsdalen valley | Statement: [Sør-Fron, hasGeographicalFeature, Gudbrandsdalen valley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gudbrandsdalen valley
Context triple: [Sør-Fron, hasGeographicalFeature, Gudbrandsdalen valley]
  • A. Gudbrandsdalen chosen
    Gudbrandsdalen is a major valley in Norway known for its dramatic landscapes, traditional farming culture, and historic role as a key inland travel route.
  • B. Verdal valley
    Verdal valley is a fertile agricultural valley in Trøndelag county, central Norway, known for its farming landscape and the town of Verdalsøra.
  • C. Gade Valley
    Gade Valley is a low-lying valley landscape in Hertfordshire, England, shaped by the River Gade and its surrounding floodplain.
  • D. Eresfjorden valley
    Eresfjorden valley is a scenic fjord valley in Møre og Romsdal county, Norway, known for its dramatic mountains, deep waters, and picturesque rural landscapes.
  • E. Saudafjorden valley
    Saudafjorden valley is a scenic fjord valley in western Norway known for its steep mountainsides, deep waters, and proximity to the industrial town of Sauda.
  • 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_69d81c6543a48190bd5ba93d7419e797 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2fa830ac81908cb7df7c9e81e42a completed April 14, 2026, 12:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdd5b98d6881908c0efd086a973af2 completed May 8, 2026, 12:23 p.m.
Created at: April 9, 2026, 10:20 p.m.