Triple

T17280843
Position Surface form Disambiguated ID Type / Status
Subject Peugeot 107 E419522 entity
Predicate relatedTo P37 FINISHED
Object Toyota Aygo E419523 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: Toyota Aygo | Statement: [Peugeot 107, relatedTo, Toyota Aygo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toyota Aygo
Context triple: [Peugeot 107, relatedTo, Toyota Aygo]
  • A. Toyota Aygo chosen
    The Toyota Aygo is a compact city car produced by Toyota, known for its small size, urban-friendly design, and shared development with PSA Peugeot Citroën models.
  • B. Renault Twingo
    The Renault Twingo is a popular city car introduced in the early 1990s, known for its compact size, distinctive styling, and practical urban-focused design.
  • C. Peugeot 107
    The Peugeot 107 is a compact city car produced by the French manufacturer Peugeot, known for its small size, fuel efficiency, and urban-friendly design.
  • D. Nissan Micra
    The Nissan Micra is a long-running subcompact hatchback car known for its small size, fuel efficiency, and popularity in urban markets worldwide.
  • E. Toyota Yaris
    The Toyota Yaris is a popular subcompact car known for its reliability, fuel efficiency, and strong reputation in global small-car markets.
  • 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_69d886da626481908a14ce7830329a35 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e43329904c8190a4cbc856b9b94ff8 completed April 19, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0179535ae08190ac0137d0f8741919 completed May 11, 2026, 6:38 a.m.
Created at: April 10, 2026, 5:40 a.m.