Triple

T13561484
Position Surface form Disambiguated ID Type / Status
Subject Volvo S60 E323918 entity
Predicate relatedModel P37 FINISHED
Object Volvo V60 E327727 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 V60 | Statement: [Volvo S60, relatedModel, Volvo V60]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Volvo V60
Context triple: [Volvo S60, relatedModel, Volvo V60]
  • A. Volvo V60 chosen
    The Volvo V60 is a premium compact estate car known for its Scandinavian design, advanced safety features, and practical yet upscale interior.
  • B. Volvo V90
    The Volvo V90 is a premium mid-size estate car known for its Scandinavian design, advanced safety features, and practical yet luxurious interior.
  • C. Volvo S60
    The Volvo S60 is a compact executive sedan known for its Scandinavian design, strong safety features, and comfortable, refined driving experience.
  • D. Volvo V50
    The Volvo V50 is a compact premium station wagon produced by the Swedish automaker Volvo, known for its safety features, practical interior, and European styling.
  • E. Volvo C30
    The Volvo C30 is a compact three-door hatchback known for its distinctive styling and pop-culture visibility, including its association with the Twilight film series.
  • 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_69d8076830b48190910a902bae5888e2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaff5219081909cf60423e79d278f completed April 12, 2026, 2:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75dad601481908de5f266f01f3f49 completed May 3, 2026, 2:37 p.m.
Created at: April 9, 2026, 9:47 p.m.