Triple

T15755530
Position Surface form Disambiguated ID Type / Status
Subject Norwegian Army Air Service E381957 entity
Predicate notableBase P7127 FINISHED
Object Gardermoen
Gardermoen is a major Norwegian air base and aviation hub that has historically served as an important military airfield for Norway.
 E1177959 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: Gardermoen | Statement: [Norwegian Army Air Service, notableBase, Gardermoen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gardermoen
Context triple: [Norwegian Army Air Service, notableBase, Gardermoen]
  • A. Gardermoen (Vestby)
    Gardermoen (Vestby) is a small village in Vestby Municipality in Viken county, Norway.
  • B. Oslo TMA
    Oslo TMA is a controlled terminal maneuvering area of Norwegian airspace surrounding Oslo, managing arriving and departing air traffic for the region’s main airports.
  • C. Oslo
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • D. Oslo
    Oslo is a collection of shared libraries that provide common code and patterns used across various OpenStack projects.
  • E. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of 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: Gardermoen
Triple: [Norwegian Army Air Service, notableBase, Gardermoen]
Generated description
Gardermoen is a major Norwegian air base and aviation hub that has historically served as an important military airfield for Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gardermoen
Target entity description: Gardermoen is a major Norwegian air base and aviation hub that has historically served as an important military airfield for Norway.
  • A. Gardermoen (Vestby)
    Gardermoen (Vestby) is a small village in Vestby Municipality in Viken county, Norway.
  • B. Oslo TMA
    Oslo TMA is a controlled terminal maneuvering area of Norwegian airspace surrounding Oslo, managing arriving and departing air traffic for the region’s main airports.
  • C. Oslo
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • D. Oslo
    Oslo is a collection of shared libraries that provide common code and patterns used across various OpenStack projects.
  • E. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e050b1ff4881909d5240d1d30f5c8b completed April 16, 2026, 3 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff998397688190a77b6a7c5b542f7e completed May 9, 2026, 8:30 p.m.
NEDg Description generation batch_69ff9a56d43c8190819deb48d59e16cb completed May 9, 2026, 8:34 p.m.
NED2 Entity disambiguation (via description) batch_69ff9acbd2b481908b9d415e26d0db81 completed May 9, 2026, 8:36 p.m.
Created at: April 10, 2026, 4:47 a.m.