Triple

T460297
Position Surface form Disambiguated ID Type / Status
Subject British American Tobacco E7321 entity
Predicate brand P1500 FINISHED
Object Velo
Velo is a nicotine pouch brand owned by British American Tobacco, marketed as a smokeless alternative to traditional cigarettes.
 E57779 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: Velo | Statement: [British American Tobacco, brand, Velo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Velo
Context triple: [British American Tobacco, brand, Velo]
  • A. Flivver
    Flivver is a colloquial nickname for the Ford Model T, the iconic early 20th-century mass-produced automobile that revolutionized personal transportation.
  • B. Sidecar
    Sidecar is a macOS feature that lets you use an iPad as a secondary display and input device for your Mac, supporting Apple Pencil and touch interactions.
  • C. Segway PT
    The Segway PT is a self-balancing, two-wheeled personal transporter that became widely known as an innovative but niche urban mobility device.
  • D. Mvezo
    Mvezo is a small rural village in South Africa’s Eastern Cape best known as the birthplace of Nelson Mandela.
  • E. Rider
    Rider is a cross-platform integrated development environment by JetBrains, widely used for .NET and C# development.
  • 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: Velo
Triple: [British American Tobacco, brand, Velo]
Generated description
Velo is a nicotine pouch brand owned by British American Tobacco, marketed as a smokeless alternative to traditional cigarettes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Velo
Target entity description: Velo is a nicotine pouch brand owned by British American Tobacco, marketed as a smokeless alternative to traditional cigarettes.
  • A. Flivver
    Flivver is a colloquial nickname for the Ford Model T, the iconic early 20th-century mass-produced automobile that revolutionized personal transportation.
  • B. Sidecar
    Sidecar is a macOS feature that lets you use an iPad as a secondary display and input device for your Mac, supporting Apple Pencil and touch interactions.
  • C. Segway PT
    The Segway PT is a self-balancing, two-wheeled personal transporter that became widely known as an innovative but niche urban mobility device.
  • D. Mvezo
    Mvezo is a small rural village in South Africa’s Eastern Cape best known as the birthplace of Nelson Mandela.
  • E. Rider
    Rider is a cross-platform integrated development environment by JetBrains, widely used for .NET and C# development.
  • 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_69a2e7e5c5bc8190a1dc8178218fba40 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2efbd6ed481909ec40f12b5b675c8 completed Feb. 28, 2026, 1:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69a44f583ea081908d92fe5b5dc4d3c0 completed March 1, 2026, 2:38 p.m.
NEDg Description generation batch_69a45150b3f8819094519329a68fb1b8 completed March 1, 2026, 2:46 p.m.
NED2 Entity disambiguation (via description) batch_69a451ab785c8190b4cab0d162b4efa8 completed March 1, 2026, 2:48 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.