Triple

T22682879
Position Surface form Disambiguated ID Type / Status
Subject Veitvet E560827 entity
Predicate hasLandmark P105 FINISHED
Object Veitvetveien
Veitvetveien is a street in the Veitvet neighborhood of Oslo, Norway, serving as one of the area’s main local thoroughfares.
 E1549408 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: Veitvetveien | Statement: [Veitvet, hasLandmark, Veitvetveien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Veitvetveien
Context triple: [Veitvet, hasLandmark, Veitvetveien]
  • A. Maridalsveien
    Maridalsveien is a major street in Oslo, Norway, running north from the city center toward the Maridalen valley and serving as an important thoroughfare in the area.
  • B. Markveien
    Markveien is a well-known street in the Grünerløkka district of Oslo, Norway, noted for its vibrant mix of shops, cafés, and urban culture.
  • C. Lysebotnvegen
    Lysebotnvegen is a scenic mountain road in Norway known for its dramatic hairpin bends, steep climbs, and panoramic views over the Lysefjord.
  • D. Munkedamsveien
    Munkedamsveien is a central street in Oslo, Norway, known for hosting major cultural venues and offices near the city’s waterfront.
  • E. Kirkeveien
    Kirkeveien is a prominent thoroughfare in Oslo, Norway, known for running through the Majorstuen area and connecting several central neighborhoods and parks.
  • 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: Veitvetveien
Triple: [Veitvet, hasLandmark, Veitvetveien]
Generated description
Veitvetveien is a street in the Veitvet neighborhood of Oslo, Norway, serving as one of the area’s main local thoroughfares.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Veitvetveien
Target entity description: Veitvetveien is a street in the Veitvet neighborhood of Oslo, Norway, serving as one of the area’s main local thoroughfares.
  • A. Maridalsveien
    Maridalsveien is a major street in Oslo, Norway, running north from the city center toward the Maridalen valley and serving as an important thoroughfare in the area.
  • B. Markveien
    Markveien is a well-known street in the Grünerløkka district of Oslo, Norway, noted for its vibrant mix of shops, cafés, and urban culture.
  • C. Lysebotnvegen
    Lysebotnvegen is a scenic mountain road in Norway known for its dramatic hairpin bends, steep climbs, and panoramic views over the Lysefjord.
  • D. Munkedamsveien
    Munkedamsveien is a central street in Oslo, Norway, known for hosting major cultural venues and offices near the city’s waterfront.
  • E. Kirkeveien
    Kirkeveien is a prominent thoroughfare in Oslo, Norway, known for running through the Majorstuen area and connecting several central neighborhoods and parks.
  • 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_69e2454d71b48190a1f80af9f82b6fcf completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1786204d88190a837a5f04e16e94c completed April 29, 2026, 3:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b73f4db988190a651faf7f454c6c8 completed May 18, 2026, 8:17 p.m.
NEDg Description generation batch_6a0b7551043c81908323a86af4db77ce completed May 18, 2026, 8:23 p.m.
NED2 Entity disambiguation (via description) batch_6a0b764c2de88190bb1024206607d107 completed May 18, 2026, 8:27 p.m.
Created at: April 17, 2026, 3:12 p.m.