Triple

T18254333
Position Surface form Disambiguated ID Type / Status
Subject Viking E437182 entity
Predicate hasParentOrganization P10 FINISHED
Object Continental AG 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: Continental AG | Statement: [Viking, hasParentOrganization, Continental AG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Continental AG
Context triple: [Viking, hasParentOrganization, Continental AG]
  • A. 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.
  • B. Continental chosen
    Continental is a major German automotive manufacturing company best known for producing tires, braking systems, and other vehicle components.
  • C. 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.
  • D. Bridgestone
    Bridgestone is a global tire and rubber company headquartered in Japan, known for its extensive involvement in motorsports and major sports sponsorships.
  • E. Otto Group
    Otto Group is a major German multinational retail and services conglomerate best known for its e-commerce, logistics, and mail-order businesses.
  • 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_69d8b913351c8190932b6a426de04b41 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4fd84b3a481908bbc1a5e5034d397 completed April 19, 2026, 4:06 p.m.
Created at: April 10, 2026, 10:33 a.m.