Triple

T5828546
Position Surface form Disambiguated ID Type / Status
Subject FA Women's League Cup E129288 entity
Predicate sponsor P67 FINISHED
Object Continental AG E95172 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: Continental AG | Statement: [FA Women's League Cup, sponsor, Continental AG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Continental AG
Context triple: [FA Women's League Cup, sponsor, Continental AG]
  • A. Continental chosen
    Continental is a major German automotive manufacturing company best known for producing tires, braking systems, and other vehicle components.
  • B. Nokian Tyres
    Nokian Tyres is a Finnish tire manufacturer best known for its high-quality winter and all-weather tires designed for challenging Nordic conditions.
  • 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. Michelin
    Michelin is a major French multinational tire manufacturer renowned for its tires, travel guides, and the Michelin star restaurant rating system.
  • E. Pirelli
    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.
  • 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_69c00849d55481908b4f9f5543e0bf6d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03467dfe48190b51757b33681bc20 completed March 22, 2026, 6:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c09863be3c8190bba357bf64e22917 completed March 23, 2026, 1:33 a.m.
Created at: March 22, 2026, 3:53 p.m.