Triple

T11639773
Position Surface form Disambiguated ID Type / Status
Subject UiT The Arctic University of Norway E276628 entity
Predicate hasCampus P116 FINISHED
Object Harstad E439363 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: Harstad | Statement: [UiT The Arctic University of Norway, hasCampus, Harstad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harstad
Context triple: [UiT The Arctic University of Norway, hasCampus, Harstad]
  • A. Harstad
    Harstad is a coastal town and municipality in Troms county, known as an important regional center in Northern Norway with a strong maritime and cultural heritage.
  • B. Kristinestad
    Kristinestad is a small coastal town in western Finland known for its well-preserved wooden old town and historic maritime character.
  • C. Tonstad
    Tonstad is a small village in Agder county, Norway, serving as the administrative and commercial center of Sirdal municipality.
  • D. Harstad municipality chosen
    Harstad municipality is a local government area in Troms county, northern Norway, centered on the coastal town of Harstad and known for its maritime industries and Arctic landscape.
  • E. Slemdal
    Slemdal is a residential neighborhood in the Vestre Aker borough of Oslo, Norway, known for its green surroundings and affluent character.
  • 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_69d6aafa51148190ab84940694c00235 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a25e90c08190b7fb73939a2be3d7 completed April 10, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee87deb3888190842bd61efd7b3989 completed April 26, 2026, 9:47 p.m.
Created at: April 8, 2026, 9:39 p.m.