Triple

T21784037
Position Surface form Disambiguated ID Type / Status
Subject Majorstuen E537788 entity
Predicate hasMainStreet P461 FINISHED
Object Kirkeveien
Kirkeveien is a prominent thoroughfare in Oslo, Norway, known for running through the Majorstuen area and connecting several central neighborhoods and parks.
 E1501892 NE FINISHED

How this triple was built (4 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: Kirkeveien | Statement: [Majorstuen, hasMainStreet, Kirkeveien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kirkeveien
Context triple: [Majorstuen, hasMainStreet, Kirkeveien]
  • A. Vålerenggata
    Vålerenggata is a street located in the Vålerenga neighborhood of Oslo, Norway, known for its traditional wooden houses and historic urban character.
  • B. Bogstadveien
    Bogstadveien is a prominent shopping and commercial street in Oslo, Norway, known for its boutiques, cafes, and central location.
  • C. Trondheimsveien
    Trondheimsveien is a major thoroughfare in Oslo, Norway, serving as an important traffic artery through the city and its northeastern districts.
  • D. Lysebotnvegen
    Lysebotnvegen is a scenic mountain road in Norway known for its dramatic hairpin bends, steep climbs, and panoramic views over the Lysefjord.
  • E. Hedmarksgata
    Hedmarksgata is a street located in the Vålerenga neighborhood of Oslo, Norway.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kirkeveien
Triple: [Majorstuen, hasMainStreet, Kirkeveien]
Generated description
Kirkeveien is a prominent thoroughfare in Oslo, Norway, known for running through the Majorstuen area and connecting several central neighborhoods and parks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kirkeveien
Target entity description: Kirkeveien is a prominent thoroughfare in Oslo, Norway, known for running through the Majorstuen area and connecting several central neighborhoods and parks.
  • A. Vålerenggata
    Vålerenggata is a street located in the Vålerenga neighborhood of Oslo, Norway, known for its traditional wooden houses and historic urban character.
  • B. Bogstadveien
    Bogstadveien is a prominent shopping and commercial street in Oslo, Norway, known for its boutiques, cafes, and central location.
  • C. Trondheimsveien
    Trondheimsveien is a major thoroughfare in Oslo, Norway, serving as an important traffic artery through the city and its northeastern districts.
  • D. Lysebotnvegen
    Lysebotnvegen is a scenic mountain road in Norway known for its dramatic hairpin bends, steep climbs, and panoramic views over the Lysefjord.
  • E. Hedmarksgata
    Hedmarksgata is a street located in the Vålerenga neighborhood of Oslo, Norway.
  • F. None of above. chosen

Provenance (5 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_69e0c47198f881908cb0d237266c10e9 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f046303d54819096b3fab4ab5678e6 completed April 28, 2026, 5:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0a3e6f77cc81909ff2ca8b6c8e57e0 completed May 17, 2026, 10:17 p.m.
NEDg Description generation batch_6a0a3f5813a081909f253f04ca218559 completed May 17, 2026, 10:21 p.m.
NED2 Entity disambiguation (via description) batch_6a0a400831d881909631e1accd5618f1 completed May 17, 2026, 10:24 p.m.
Created at: April 16, 2026, 6:52 p.m.