Triple

T20706764
Position Surface form Disambiguated ID Type / Status
Subject Frostating Court of Appeal E508921 entity
Predicate buildingLocation P40 FINISHED
Object Trondheim, Norway 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: Trondheim, Norway | Statement: [Frostating Court of Appeal, buildingLocation, Trondheim, Norway]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trondheim, Norway
Context triple: [Frostating Court of Appeal, buildingLocation, Trondheim, Norway]
  • A. Trondheim chosen
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • B. Oslo
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • C. Oslo
    Oslo is a collection of shared libraries that provide common code and patterns used across various OpenStack projects.
  • D. Stavanger
    Stavanger is a coastal city in southwestern Norway known for its oil industry hub status, historic wooden houses, and proximity to natural attractions like the Lysefjord and Preikestolen.
  • E. Bergen, Sweden
    Bergen, Sweden is a small locality in Västra Götaland County known for its rural character and twinning relationship with Bergen, Germany.
  • 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_69e0b4c2b2a481909e31e9cb8f81ab55 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6c1917ce08190a54720d4d5b0a02c completed April 21, 2026, 12:15 a.m.
Created at: April 16, 2026, 12:13 p.m.