Triple

T4201761
Position Surface form Disambiguated ID Type / Status
Subject Hovdetoppen E86082 entity
Predicate locatedIn P40 FINISHED
Object Gjøvik E84018 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: Gjøvik | Statement: [Hovdetoppen, locatedIn, Gjøvik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gjøvik
Context triple: [Hovdetoppen, locatedIn, Gjøvik]
  • A. Gjøvik chosen
    Gjøvik is a town and municipality in Innlandet county, Norway, known for its location along Lake Mjøsa and its mix of industrial heritage and modern sports and cultural facilities.
  • B. Lørenskog
    Lørenskog is a suburban municipality in Viken county, Norway, located just east of Oslo and known for its residential areas and commercial centers.
  • C. Drammen
    Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
  • D. Bærum
    Bærum is a wealthy suburban municipality just west of Oslo, Norway, known for its high standard of living and residential communities.
  • E. Porsgrunn
    Porsgrunn is an industrial and port city in Telemark county in southeastern Norway, known for its porcelain production and location along the Telemark Canal.
  • 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_69aed93b89f48190a31f6d57c760e42f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af037da30481908106b27a88d59140 completed March 9, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5962296b8819084b91de3f48b7658 completed March 14, 2026, 5:08 p.m.
Created at: March 9, 2026, 3:49 p.m.