Triple

T9076143
Position Surface form Disambiguated ID Type / Status
Subject Audi Q7 E217487 entity
Predicate competitor P1375 FINISHED
Object Volvo XC90 E316544 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 XC90 | Statement: [Audi Q7, competitor, Volvo XC90]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Volvo XC90
Context triple: [Audi Q7, competitor, Volvo XC90]
  • A. Volvo XC90 chosen
    The Volvo XC90 is a mid-size luxury SUV known for its Scandinavian design, advanced safety features, and family-friendly practicality.
  • B. Volvo XC60
    The Volvo XC60 is a compact luxury crossover SUV known for its Scandinavian design, advanced safety features, and comfortable, family-oriented driving experience.
  • C. Volvo S90
    The Volvo S90 is a mid-size luxury sedan known for its Scandinavian design, advanced safety features, and comfort-focused driving experience.
  • D. 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.
  • 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_69ca83d6c14c8190bc056d927f00a2a2 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc95c53274819099b3b3047bfe8cc8 completed April 1, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69cffe0fade4819093e4d1d91aca1d3f completed April 3, 2026, 5:51 p.m.
Created at: March 30, 2026, 7:12 p.m.