Triple

T4668041
Position Surface form Disambiguated ID Type / Status
Subject Peugeot 208 E102895 entity
Predicate predecessor P97 FINISHED
Object Peugeot 207 E99953 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 207 | Statement: [Peugeot 208, predecessor, Peugeot 207]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peugeot 207
Context triple: [Peugeot 208, predecessor, Peugeot 207]
  • A. Peugeot 207 chosen
    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.
  • B. 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.
  • C. Peugeot 206
    The Peugeot 206 is a popular supermini car produced by the French manufacturer Peugeot, known for its stylish design and strong sales success in the late 1990s and 2000s.
  • D. 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.
  • E. 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.
  • 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_69bd43d9cba4819086c1ab1c2d9d2133 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd633ec8b08190bf8ffd4c3b946f61 completed March 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69be038912488190a109d4ce624b813d completed March 21, 2026, 2:33 a.m.
Created at: March 20, 2026, 1:15 p.m.