Triple

T20634137
Position Surface form Disambiguated ID Type / Status
Subject CMF-B platform E507033 entity
Predicate underpins P3636 FINISHED
Object Renault Clio V NE NERFINISHED

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 Clio V | Statement: [CMF-B platform, underpins, Renault Clio V]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Renault Clio V
Context triple: [CMF-B platform, underpins, Renault Clio V]
  • A. Renault Clio chosen
    The Renault Clio is a popular supermini car produced by French manufacturer Renault, known for its practicality, efficiency, and strong sales across Europe.
  • B. Renault Mégane
    The Renault Mégane is a popular compact family car produced by French automaker Renault, known for its practical design, comfort, and range of body styles and powertrains.
  • C. Peugeot 208
    The Peugeot 208 is a popular supermini hatchback produced by the French automaker Peugeot, known for its stylish design, efficient engines, and modern technology features.
  • D. Citroën Nemo
    The Citroën Nemo is a compact light commercial van designed for urban delivery and small business use, developed in collaboration with Fiat and Peugeot.
  • E. Renault 21
    The Renault 21 is a mid-size family car produced by the French manufacturer Renault in the late 1980s and early 1990s, known for its practical design and wide range of body styles and engines.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4bd4a0081908d4e97a590a33fb2 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6ad0d808c81908a60abd02a22ed92 completed April 20, 2026, 10:47 p.m.
Created at: April 16, 2026, 11:42 a.m.