Triple

T3016304
Position Surface form Disambiguated ID Type / Status
Subject National League North E82343 entity
Predicate sponsor P67 FINISHED
Object Vanarama
Vanarama is a UK-based vehicle leasing and finance company known for its prominent sponsorship of English football leagues and clubs.
 E318154 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: Vanarama | Statement: [National League North, sponsor, Vanarama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vanarama
Context triple: [National League North, sponsor, Vanarama]
  • A. Tull
    Tull is a surname most prominently associated with American film producer and entrepreneur Thomas Tull.
  • B. Banwen
    Banwen is a small village in South Wales, known historically for its coal mining heritage and location near the upper Dulais Valley.
  • C. Vassa
    Vassa is the traditional Buddhist rainy-season retreat during which monks remain in one place for intensive meditation and study.
  • D. Vivarais
    Vivarais is a historical region in south-central France, known for its rugged landscapes, part of the broader Massif Central, and its traditional rural culture.
  • E. Faventia
    Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
  • 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: Vanarama
Triple: [National League North, sponsor, Vanarama]
Generated description
Vanarama is a UK-based vehicle leasing and finance company known for its prominent sponsorship of English football leagues and clubs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vanarama
Target entity description: Vanarama is a UK-based vehicle leasing and finance company known for its prominent sponsorship of English football leagues and clubs.
  • A. Tull
    Tull is a surname most prominently associated with American film producer and entrepreneur Thomas Tull.
  • B. Banwen
    Banwen is a small village in South Wales, known historically for its coal mining heritage and location near the upper Dulais Valley.
  • C. Vassa
    Vassa is the traditional Buddhist rainy-season retreat during which monks remain in one place for intensive meditation and study.
  • D. Vivarais
    Vivarais is a historical region in south-central France, known for its rugged landscapes, part of the broader Massif Central, and its traditional rural culture.
  • E. Faventia
    Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
  • 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_69ad8b1eb53481908c39bbcd1ec104b2 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a6c56708190b7d8d08bca727cc1 completed March 8, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e6eac1481909d56844e53c37b59 completed March 11, 2026, 8:57 a.m.
NEDg Description generation batch_69b12f26a8d08190be6023fb7e3ddee9 completed March 11, 2026, 9 a.m.
NED2 Entity disambiguation (via description) batch_69b1cb268d9881908766e50524b208cc completed March 11, 2026, 8:05 p.m.
Created at: March 8, 2026, 3 p.m.