Triple

T4497851
Position Surface form Disambiguated ID Type / Status
Subject Renault E100742 entity
Predicate notableModel P1503 FINISHED
Object Renault Captur E392657 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: Renault Captur | Statement: [Renault, notableModel, Renault Captur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Renault Captur
Context triple: [Renault, notableModel, Renault Captur]
  • A. Renault Captur chosen
    The Renault Captur is a compact crossover SUV known for its stylish design, urban-friendly size, and practical interior, positioned in the popular small SUV segment.
  • B. Peugeot 3008
    The Peugeot 3008 is a compact crossover SUV known for its distinctive design, practical interior, and advanced technology features.
  • C. Peugeot 2008
    The Peugeot 2008 is a subcompact crossover SUV produced by the French automaker Peugeot, known for its urban-friendly size, modern styling, and efficient engines.
  • D. Citroën C5 X
    The Citroën C5 X is a large crossover-style flagship model from Citroën that blends elements of a sedan, estate, and SUV, emphasizing comfort and distinctive design.
  • E. Peugeot 5008
    The Peugeot 5008 is a mid-size crossover SUV, originally launched as an MPV, known for its seven-seat practicality and modern French 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_69bd43cdf15081909a4fa2585ff63b3e completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd56c065e88190934eb0b1632d79bb completed March 20, 2026, 2:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd67c7da888190a60bd738e53156ed completed March 20, 2026, 3:29 p.m.
Created at: March 20, 2026, 1 p.m.