Triple

T4305892
Position Surface form Disambiguated ID Type / Status
Subject Peugeot 207 E99953 entity
Predicate relatedModel P37 FINISHED
Object Citroën C3 E395012 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: Citroën C3 | Statement: [Peugeot 207, relatedModel, Citroën C3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Citroën C3
Context triple: [Peugeot 207, relatedModel, Citroën C3]
  • A. Citroën C3 chosen
    The Citroën C3 is a supermini car produced by the French manufacturer Citroën, known for its distinctive styling and practical, city-friendly design.
  • B. Citroën C4
    The Citroën C4 is a compact family car produced by the French automaker Citroën, known for its distinctive styling and comfort-focused design.
  • C. Citroën C2
    The Citroën C2 is a small three-door supermini car produced by the French manufacturer Citroën in the 2000s, known for its compact dimensions and youthful, sporty styling.
  • D. Citroën C1
    The Citroën C1 is a compact city car produced by the French automaker Citroën, known for its small size, efficiency, and urban-friendly design.
  • E. Renault Clio
    The Renault Clio is a popular supermini car produced by French manufacturer Renault, known for its practicality, efficiency, and strong sales across Europe.
  • 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_69b345528ebc8190b5abc7e95094792d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b350ba57ec8190afda7d8318e5d2d0 completed March 12, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5f5bf4dd48190b84d8488a4f196a8 completed March 14, 2026, 11:56 p.m.
Created at: March 12, 2026, 11:09 p.m.