Triple

T7937946
Position Surface form Disambiguated ID Type / Status
Subject OpenStack E184327 entity
Predicate component P35 FINISHED
Object Oslo
Oslo is a collection of shared libraries that provide common code and patterns used across various OpenStack projects.
 E705948 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: [OpenStack, component, Oslo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Oslo
Context triple: [OpenStack, component, 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 a city in western Germany, historically notable as the site of the 1759 Battle of Bergen during the Seven Years' War.
  • D. 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.
  • E. Bergens
    The Bergens are a race of gloomy, troll-eating creatures who serve as the primary villains in the animated film "Trolls."
  • 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: [OpenStack, component, Oslo]
Generated description
Oslo is a collection of shared libraries that provide common code and patterns used across various OpenStack projects.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Oslo
Target entity description: Oslo is a collection of shared libraries that provide common code and patterns used across various OpenStack projects.
  • 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 a city in western Germany, historically notable as the site of the 1759 Battle of Bergen during the Seven Years' War.
  • D. 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.
  • E. Bergens
    The Bergens are a race of gloomy, troll-eating creatures who serve as the primary villains in the animated film "Trolls."
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3aef2394819086eea1f6ab117aed completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc55f5c7408190823dbe7c59d61ead completed March 31, 2026, 11:17 p.m.
NEDg Description generation batch_69cc5822581481908a143376bee599ec completed March 31, 2026, 11:26 p.m.
NED2 Entity disambiguation (via description) batch_69cc58f549388190ba6c8b41c0820cd6 completed March 31, 2026, 11:29 p.m.
Created at: March 30, 2026, 5:08 p.m.