Triple

T13625099
Position Surface form Disambiguated ID Type / Status
Subject Aurora Innovation E325557 entity
Predicate partner P1136 FINISHED
Object Volvo Group E142854 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: Volvo Group | Statement: [Aurora Innovation, partner, Volvo Group]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Volvo Group
Context triple: [Aurora Innovation, partner, Volvo Group]
  • A. Volvo Group chosen
    Volvo Group is a Swedish multinational manufacturing company best known for producing trucks, buses, construction equipment, and marine and industrial engines.
  • B. Volvo Cars
    Volvo Cars is a Swedish automotive manufacturer known for its focus on safety, practical design, and premium vehicles.
  • C. Scania
    Scania is a Swedish manufacturer renowned for its heavy trucks, buses, and industrial and marine engines.
  • D. Scania
    Scania is a historical province in southern Sweden known for its fertile farmland, coastal landscapes, and former status as part of Denmark.
  • E. Daimler
    Daimler is a historic British luxury automobile manufacturer renowned for producing high-end saloon cars and limousines, particularly favored by royalty and official state fleets.
  • 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_69d8076aae28819092cf636190ee5529 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbbe9c72c88190be3d7a3f2e96afbc completed April 12, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd27f43bf081908dea65dc05f7c1a2 completed May 8, 2026, 12:01 a.m.
Created at: April 9, 2026, 9:50 p.m.