Triple

T14440365
Position Surface form Disambiguated ID Type / Status
Subject Norwegian Computing Center E358069 entity
Predicate locatedIn P40 FINISHED
Object Gaustad E30482 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: Gaustad | Statement: [Norwegian Computing Center, locatedIn, Gaustad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gaustad
Context triple: [Norwegian Computing Center, locatedIn, Gaustad]
  • A. Gaustad chosen
    Gaustad is a district in Oslo, Norway, known for hosting major academic and research institutions, including parts of the University of Oslo campus.
  • B. Verdal
    Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
  • C. Nissedal
    Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
  • D. Ringerike
    Ringerike is a historic district and municipality in southeastern Norway known for its rich Viking-age heritage and distinctive cultural traditions.
  • E. Svarstad
    Svarstad is a Norwegian surname associated with individuals such as Maren Svarstad.
  • 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_69d8279402a88190821ffa39ae15bccf completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de914c1398819090fa2a74d257ba3e completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe9db810c481908dde925ff90f3fa0 completed May 9, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:18 a.m.