Triple

T2576114
Position Surface form Disambiguated ID Type / Status
Subject Vuse E57777 entity
Predicate hasCompetitor P1375 FINISHED
Object Blu
Blu is a popular electronic cigarette and vaping brand known for its range of rechargeable and disposable e-cigarette products.
 E278896 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: Blu | Statement: [Vuse, hasCompetitor, Blu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Blu
Context triple: [Vuse, hasCompetitor, Blu]
  • A. Blum
    Blum is a surname of German and Jewish origin borne by various notable individuals across fields such as mathematics, politics, and the arts.
  • B. Blix
    Blix is a Swedish surname most notably associated with Hans Blix, the former head of the International Atomic Energy Agency and UN weapons inspector.
  • C. Blau
    The Blau is a small river in the German state of Baden-Württemberg that flows through the city of Blaustein before joining the Danube.
  • D. Luma
    Luma is a small, star-shaped celestial creature from the Super Mario series, known for its cute appearance and connection to Rosalina and the cosmos.
  • E. Blatch
    Blatch is the surname of Nora Stanton Blatch, an early 20th-century American civil engineer, suffragist, and women's rights activist.
  • 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: Blu
Triple: [Vuse, hasCompetitor, Blu]
Generated description
Blu is a popular electronic cigarette and vaping brand known for its range of rechargeable and disposable e-cigarette products.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Blu
Target entity description: Blu is a popular electronic cigarette and vaping brand known for its range of rechargeable and disposable e-cigarette products.
  • A. Blum
    Blum is a surname of German and Jewish origin borne by various notable individuals across fields such as mathematics, politics, and the arts.
  • B. Blix
    Blix is a Swedish surname most notably associated with Hans Blix, the former head of the International Atomic Energy Agency and UN weapons inspector.
  • C. Blau
    The Blau is a small river in the German state of Baden-Württemberg that flows through the city of Blaustein before joining the Danube.
  • D. Luma
    Luma is a small, star-shaped celestial creature from the Super Mario series, known for its cute appearance and connection to Rosalina and the cosmos.
  • E. Blatch
    Blatch is the surname of Nora Stanton Blatch, an early 20th-century American civil engineer, suffragist, and women's rights activist.
  • 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_69ab4a51410081908501dcf8bad9adc4 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd3a606e481909bcea46de468bb99 completed March 7, 2026, 7:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69af657413908190a03b9dd8dc40b2e4 completed March 10, 2026, 12:27 a.m.
NEDg Description generation batch_69af67cbaf388190b5bb447af2a8e941 completed March 10, 2026, 12:37 a.m.
NED2 Entity disambiguation (via description) batch_69af682b38d08190bba53245e813f044 completed March 10, 2026, 12:39 a.m.
Created at: March 6, 2026, 9:49 p.m.