Triple

T9197821
Position Surface form Disambiguated ID Type / Status
Subject Audi A6 E220759 entity
Predicate competitor P1375 FINISHED
Object Volvo S90 E324243 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 S90 | Statement: [Audi A6, competitor, Volvo S90]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Volvo S90
Context triple: [Audi A6, competitor, Volvo S90]
  • A. Volvo S90 chosen
    The Volvo S90 is a mid-size luxury sedan known for its Scandinavian design, advanced safety features, and comfort-focused driving experience.
  • 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 XC90
    The Volvo XC90 is a mid-size luxury SUV known for its Scandinavian design, advanced safety features, and family-friendly practicality.
  • D. Volvo S60
    The Volvo S60 is a compact executive sedan known for its Scandinavian design, strong safety features, and comfortable, refined driving experience.
  • E. Volvo V60
    The Volvo V60 is a premium compact estate car known for its Scandinavian design, advanced safety features, and practical yet upscale interior.
  • 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_69ca83e7ba70819088b74866d9da2c30 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd87f50e88190940e73af1deda747 completed April 1, 2026, 8:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05c3b1af48190bb03af15232c510d completed April 4, 2026, 12:32 a.m.
Created at: March 30, 2026, 7:25 p.m.