Triple

T17370997
Position Surface form Disambiguated ID Type / Status
Subject Krødsherad E422312 entity
Predicate borderedBy P224 FINISHED
Object Modum NE ONNED1

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: Modum | Statement: [Krødsherad, borderedBy, Modum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Modum
Context triple: [Krødsherad, borderedBy, Modum]
  • A. Modum chosen
    Modum is a municipality in Buskerud, Norway, known for its rural landscapes, historic industrial sites, and recreational areas such as the Vikersund ski flying hill.
  • B. Moudon
    Moudon is a historic town and former district capital in the canton of Vaud, Switzerland, known for its medieval old town and location in the Broye valley.
  • C. Meliden
    Meliden is a village in Denbighshire, North Wales, situated inland from the coastal town of Prestatyn.
  • D. Modimolle
    Modimolle is a town in South Africa’s Limpopo province known as a commercial and agricultural hub and a gateway to the surrounding Waterberg bushveld and wildlife areas.
  • E. Mosen
    Mosen is a small Swiss village in the canton of Lucerne, situated in a rural lakeside setting in central Switzerland.
  • 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_69d889d6535c81908be333c01deaec4e completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a68ff448190b505861e56df5b6d completed April 19, 2026, 2:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a019568a27c8190af1bbe6db75f3e6f in_progress May 11, 2026, 8:38 a.m.
Created at: April 10, 2026, 5:44 a.m.