Triple

T23030127
Position Surface form Disambiguated ID Type / Status
Subject Bogstadveien E573433 entity
Predicate connectsTo P845 FINISHED
Object Hegdehaugsveien
Hegdehaugsveien is a well-known shopping and commercial street in central Oslo, Norway, forming a continuous retail thoroughfare with Bogstadveien.
 E1570453 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: Hegdehaugsveien | Statement: [Bogstadveien, connectsTo, Hegdehaugsveien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hegdehaugsveien
Context triple: [Bogstadveien, connectsTo, Hegdehaugsveien]
  • 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. 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. Munkedamsveien
    Munkedamsveien is a central street in Oslo, Norway, known for hosting major cultural venues and offices near the city’s waterfront.
  • 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: Hegdehaugsveien
Triple: [Bogstadveien, connectsTo, Hegdehaugsveien]
Generated description
Hegdehaugsveien is a well-known shopping and commercial street in central Oslo, Norway, forming a continuous retail thoroughfare with Bogstadveien.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hegdehaugsveien
Target entity description: Hegdehaugsveien is a well-known shopping and commercial street in central Oslo, Norway, forming a continuous retail thoroughfare with Bogstadveien.
  • 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. 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. Munkedamsveien
    Munkedamsveien is a central street in Oslo, Norway, known for hosting major cultural venues and offices near the city’s waterfront.
  • 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_69e245b911188190bc3d96326c847969 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f184803e908190b1e58545b9c3d587 completed April 29, 2026, 4:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c159dd33881909a7cf4c1c218ba33 completed May 19, 2026, 7:47 a.m.
NEDg Description generation batch_6a0c19ba2cd88190aeffda94f9c2c361 completed May 19, 2026, 8:05 a.m.
NED2 Entity disambiguation (via description) batch_6a0c1b6bad048190ad23d93e3f95a75d completed May 19, 2026, 8:12 a.m.
Created at: April 17, 2026, 3:53 p.m.