Triple

T16420120
Position Surface form Disambiguated ID Type / Status
Subject DS 3 Crossback E398794 entity
Predicate assemblyLocation P40 FINISHED
Object Poissy, France E1211491 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: Poissy, France | Statement: [DS 3 Crossback, assemblyLocation, Poissy, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Poissy, France
Context triple: [DS 3 Crossback, assemblyLocation, Poissy, France]
  • A. Poissy, France chosen
    Poissy, France is a commune in the western suburbs of Paris known for its historic architecture and major automobile manufacturing facilities.
  • B. Vaucresson, France
    Vaucresson, France is a small, affluent suburban commune in the western outskirts of Paris, known for its residential character and proximity to the capital.
  • C. Marnes-la-Coquette, France
    Marnes-la-Coquette, France is a small, affluent commune in the western suburbs of Paris, historically noted as the place where the renowned scientist Louis Pasteur died.
  • D. Blois, France
    Blois, France is a historic city on the Loire River known for its Renaissance château and as the birthplace of King Stephen of England.
  • E. Maisons-Laffitte, France
    Maisons-Laffitte, France is a suburban town northwest of Paris known for its historic château and prominent horse-racing track.
  • 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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e328f5c1bc8190a679f35bd6c0bc97 completed April 18, 2026, 6:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00457f60c081908f4e46993780ac09 completed May 10, 2026, 8:44 a.m.
Created at: April 10, 2026, 5:09 a.m.