Triple

T22078413
Position Surface form Disambiguated ID Type / Status
Subject Vika E545581 entity
Predicate hasStreet P959 FINISHED
Object Munkedamsveien 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: Munkedamsveien | Statement: [Vika, hasStreet, Munkedamsveien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Munkedamsveien
Context triple: [Vika, hasStreet, Munkedamsveien]
  • A. Munkedamsveien chosen
    Munkedamsveien is a central street in Oslo, Norway, known for hosting major cultural venues and offices near the city’s waterfront.
  • B. Lysebotnvegen
    Lysebotnvegen is a scenic mountain road in Norway known for its dramatic hairpin bends, steep climbs, and panoramic views over the Lysefjord.
  • C. Hedmarksgata
    Hedmarksgata is a street located in the Vålerenga neighborhood of Oslo, Norway.
  • D. Kirkeveien
    Kirkeveien is a prominent thoroughfare in Oslo, Norway, known for running through the Majorstuen area and connecting several central neighborhoods and parks.
  • E. Møllergata
    Møllergata is a central street in Oslo, Norway, known for its historic buildings and proximity to key political and commercial areas.
  • 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_69e11e3523488190badd54b5d580c00d completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f128b43df0819090c248ded98fad12 completed April 28, 2026, 9:37 p.m.
Created at: April 16, 2026, 8:28 p.m.