Triple

T2206713
Position Surface form Disambiguated ID Type / Status
Subject Viken county E50816 entity
Predicate capital P234 FINISHED
Object Oslo
Oslo is the capital and largest city of Norway, known for its maritime history, modern architecture, and surrounding fjords and forests.
 E3654 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: Oslo | Statement: [Viken county, capital, Oslo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Oslo
Context triple: [Viken county, capital, Oslo]
  • A. Oslo
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • B. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • C. Bergen
    Bergen is Norway's second-largest city, renowned for its historic harbor, surrounding mountains and fjords, and role as a former Hanseatic trading hub.
  • D. Stavanger
    Stavanger is a coastal city in southwestern Norway known for its oil industry hub status, historic wooden houses, and proximity to natural attractions like the Lysefjord and Preikestolen.
  • E. Tromsø
    Tromsø is a city in northern Norway known for its Arctic location, vibrant cultural scene, and prominence as a viewing spot for the Northern Lights.
  • 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: Oslo
Triple: [Viken county, capital, Oslo]
Generated description
Oslo is the capital and largest city of Norway, known for its maritime history, modern architecture, and surrounding fjords and forests.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Oslo
Target entity description: Oslo is the capital and largest city of Norway, known for its maritime history, modern architecture, and surrounding fjords and forests.
  • A. Oslo chosen
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • B. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • C. Bergen
    Bergen is Norway's second-largest city, renowned for its historic harbor, surrounding mountains and fjords, and role as a former Hanseatic trading hub.
  • D. Stavanger
    Stavanger is a coastal city in southwestern Norway known for its oil industry hub status, historic wooden houses, and proximity to natural attractions like the Lysefjord and Preikestolen.
  • E. Tromsø
    Tromsø is a city in northern Norway known for its Arctic location, vibrant cultural scene, and prominence as a viewing spot for the Northern Lights.
  • F. None of above.

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_69a88b06709c8190978fb2418470d1b6 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abbfca300c81908b33debafa77d152 completed March 7, 2026, 6:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebef5ac7c81908015969c04fcc425 completed March 9, 2026, 12:37 p.m.
NEDg Description generation batch_69aec38a3b8081909f6a8474e59f7575 completed March 9, 2026, 12:56 p.m.
NED2 Entity disambiguation (via description) batch_69aec3e8aa9c8190b9930f1af57b8380 completed March 9, 2026, 12:58 p.m.
Created at: March 4, 2026, 7:46 p.m.