Triple

T13893682
Position Surface form Disambiguated ID Type / Status
Subject Lexus ES E334033 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: [Lexus ES, competitor, Volvo S90]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Volvo S90
Context triple: [Lexus ES, 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_69d81c5dd2d48190b7a5fc1e009de936 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de23a741908190bdf46d76c5f1411a completed April 14, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c71ca8a881908ac02687fbfe62fb completed May 3, 2026, 10:07 p.m.
Created at: April 9, 2026, 10:15 p.m.