Triple

T2128692
Position Surface form Disambiguated ID Type / Status
Subject Goodyear Tire & Rubber Company E46483 entity
Predicate competitor P1375 FINISHED
Object Pirelli E188558 NE FINISHED

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: [Goodyear Tire & Rubber Company, competitor, Pirelli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pirelli
Context triple: [Goodyear Tire & Rubber Company, competitor, 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
    Continental is a major German automotive manufacturing company best known for producing tires, braking systems, and other vehicle components.
  • E. Firestone
    Firestone is a major American tire brand known for supplying high-performance racing tires, particularly in open-wheel series like IndyCar.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a88a1626548190ae59a5028c3baa8e completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbb7659f48190871cb27faf47e18a completed March 7, 2026, 5:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5d8e61d48190af0becdc5a040cd9 completed March 9, 2026, 5:41 a.m.
Created at: March 4, 2026, 7:44 p.m.