Triple

T7765853
Position Surface form Disambiguated ID Type / Status
Subject Akersneset E176142 entity
Predicate isUrbanFeatureOf P1495 FINISHED
Object Oslo city centre E150936 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: Oslo city centre | Statement: [Akersneset, isUrbanFeatureOf, Oslo city centre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oslo city centre
Context triple: [Akersneset, isUrbanFeatureOf, Oslo city centre]
  • 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. Majorstuen, Oslo
    Majorstuen is a central neighborhood in Oslo, Norway, known for its busy transport hub, shopping streets, and cultural institutions.
  • D. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • E. Oslo East
    Oslo East is the eastern part of Norway’s capital city, often associated with working-class neighborhoods, cultural diversity, and a strong local football supporter culture.
  • 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_69c69962923c8190ac74d28b4f9fe0a0 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7043279748190b30882e9cc6cca54 completed March 27, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c91f4fb010819080ced464e4a71658 completed March 29, 2026, 12:47 p.m.
Created at: March 27, 2026, 4:09 p.m.