Triple

T17761616
Position Surface form Disambiguated ID Type / Status
Subject Lotus F1 Team E443388 entity
Predicate usedTyres P30565 FINISHED
Object Pirelli NE NERFINISHED

How this triple was built (2 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: Pirelli | Statement: [Lotus F1 Team, usedTyres, Pirelli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pirelli
Context triple: [Lotus F1 Team, usedTyres, Pirelli]
  • A. Pirelli chosen
    Pirelli is an Italian multinational company best known as one of the world’s leading manufacturers of high-performance tyres, particularly in motorsport and premium road vehicles.
  • B. Michelin
    Michelin is a major French multinational tire manufacturer renowned for its tires, travel guides, and the Michelin star restaurant rating system.
  • C. Bridgestone
    Bridgestone is a global tire and rubber company headquartered in Japan, known for its extensive involvement in motorsports and major sports sponsorships.
  • D. Continental Motors
    Continental Motors is an American manufacturer best known for producing aircraft and military vehicle engines, including powerplants for tanks and other armored vehicles.
  • E. Pirelli DP-L10
    The Pirelli DP-L10 is a GSM mobile phone handset commonly used as a low-cost, supported platform for open-source baseband experimentation and development.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9edf16c8190a59ebd245d378f4f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e485f7a8e08190a4a6b8368b70c381 completed April 19, 2026, 7:36 a.m.
Created at: April 10, 2026, 10:11 a.m.