Triple

T4497834
Position Surface form Disambiguated ID Type / Status
Subject Renault E100742 entity
Predicate brand P1500 FINISHED
Object Renault E100742 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 | Statement: [Renault, brand, Renault]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Renault
Context triple: [Renault, brand, Renault]
  • A. Renault chosen
    Renault is a major French automobile manufacturer known for producing a wide range of passenger cars, commercial vehicles, and electric vehicles sold worldwide.
  • B. Peugeot
    Peugeot is a historic French automobile manufacturer known for producing a wide range of passenger cars and commercial vehicles, now operating as a core brand within the multinational automotive group Stellantis.
  • C. Citroën
    Citroën is a historic French automobile manufacturer known for its innovative engineering and distinctive car designs.
  • D. DS Automobiles
    DS Automobiles is a French premium automotive brand known for its avant-garde design, advanced technology, and luxury-focused vehicles.
  • E. Levie Citroen
    Levie Citroen was a member of the Citroën family, related to André Citroën, the founder of the French automobile manufacturer Citroën.
  • 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.