Triple

T19974257
Position Surface form Disambiguated ID Type / Status
Subject Stor-Elvdal E493646 entity
Predicate borders P224 FINISHED
Object Åmot NE NERFINISHED

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: Åmot | Statement: [Stor-Elvdal, borders, Åmot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Åmot
Context triple: [Stor-Elvdal, borders, Åmot]
  • A. Åmot
    Åmot is a small village in Vinje Municipality in Vestfold og Telemark county, Norway, known for its rural setting in the mountainous Telemark region.
  • B. Åmot chosen
    Åmot is a rural municipality in Innlandet county in eastern Norway, known for its forests, rivers, and outdoor recreation.
  • C. Åmot municipality
    Åmot municipality is a rural municipality in Innlandet county, Norway, known for its vast forests, rivers, and outdoor recreation opportunities.
  • D. Åmål
    Åmål is a small town in western Sweden known for its picturesque lakeside setting and as the backdrop of the film "Show Me Love" (Fucking Åmål).
  • E. Andrott
    Andrott is a major inhabited island and urban center in the Lakshadweep archipelago of India, known for its dense population and traditional coastal communities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626a67648190af9653832a3aeced completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e65bcb72048190aedb4f085ace0493 completed April 20, 2026, 5 p.m.
Created at: April 11, 2026, 3:23 p.m.