Triple

T7392650
Position Surface form Disambiguated ID Type / Status
Subject Opel Corsa E170538 entity
Predicate competitor P1375 FINISHED
Object Peugeot 208 E102895 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: Peugeot 208 | Statement: [Opel Corsa, competitor, Peugeot 208]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peugeot 208
Context triple: [Opel Corsa, competitor, Peugeot 208]
  • A. Peugeot 208 chosen
    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.
  • B. 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.
  • C. Peugeot 308
    The Peugeot 308 is a compact family hatchback produced by the French automaker Peugeot, known for its stylish design, efficient engines, and comfortable ride.
  • D. Peugeot 207
    The Peugeot 207 is a supermini car produced by the French manufacturer Peugeot, introduced in the mid-2000s as the successor to the popular Peugeot 206.
  • E. 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.
  • 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_69c68a5e2c9081909e713ce866e0060a completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f224790c819099ceb7c7ac8d00f6 completed March 27, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c81ecf65388190a149efc77aedcd91 completed March 28, 2026, 6:32 p.m.
Created at: March 27, 2026, 3:09 p.m.