Triple

T13670210
Position Surface form Disambiguated ID Type / Status
Subject Volvo V60 E327727 entity
Predicate relatedModel P37 FINISHED
Object Volvo S60 E323918 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 S60 | Statement: [Volvo V60, relatedModel, Volvo S60]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Volvo S60
Context triple: [Volvo V60, relatedModel, Volvo S60]
  • A. Volvo S60 chosen
    The Volvo S60 is a compact executive sedan known for its Scandinavian design, strong safety features, and comfortable, refined driving experience.
  • B. Volvo S70
    The Volvo S70 is a mid-size executive sedan produced by the Swedish automaker Volvo from the late 1990s to early 2000s, known for its safety, comfort, and understated design.
  • C. Volvo V60
    The Volvo V60 is a premium compact estate car known for its Scandinavian design, advanced safety features, and practical yet upscale interior.
  • D. Volvo S90
    The Volvo S90 is a mid-size luxury sedan known for its Scandinavian design, advanced safety features, and comfort-focused driving experience.
  • E. 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.
  • 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc6599c248190b7f134b5b9947a23 completed April 12, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7943bfaf0819097410e901847d77c completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:53 p.m.