Triple

T22387556
Position Surface form Disambiguated ID Type / Status
Subject Grefsen E553432 entity
Predicate hasViewOf P854 FINISHED
Object Oslo city center 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: Oslo city center | Statement: [Grefsen, hasViewOf, Oslo city center]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oslo city center
Context triple: [Grefsen, hasViewOf, Oslo city center]
  • A. Sentrum, Oslo chosen
    Sentrum is the central borough of Oslo, Norway, encompassing the city’s main downtown area, key commercial districts, and major transport hubs.
  • 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. Central Oslo
    Central Oslo is the dense, historic core of Norway’s capital city, known for its major cultural institutions, shopping streets, and key government and business districts.
  • E. Majorstuen, Oslo
    Majorstuen is a central neighborhood in Oslo, Norway, known for its busy transport hub, shopping streets, and cultural institutions.
  • 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_69e11e4cf87c8190a1ff474daec326b7 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15857fb588190b8180963aedd69c0 completed April 29, 2026, 1:01 a.m.
Created at: April 16, 2026, 8:45 p.m.