Triple

T6357602
Position Surface form Disambiguated ID Type / Status
Subject Mathias Vicherat E143030 entity
Predicate name P16 FINISHED
Object Mathias Vicherat E143030 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: Mathias Vicherat | Statement: [Mathias Vicherat, name, Mathias Vicherat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mathias Vicherat
Context triple: [Mathias Vicherat, name, Mathias Vicherat]
  • A. Mathias Vicherat chosen
    Mathias Vicherat is a French executive and public administrator who serves as the president of the prestigious political science university Sciences Po in Paris.
  • B. Mathieu Klein
    Mathieu Klein is a French politician known for serving as the mayor of the city of Nancy.
  • C. Mathieu Froment
    Mathieu Froment is the central character of Émile Zola’s novel "Fécondité," embodying the author’s exploration of family, morality, and social responsibility in turn-of-the-century France.
  • D. Florian Seiche
    Florian Seiche is a German business executive best known as a co-founder and former CEO of HMD Global, the company behind modern Nokia-branded smartphones.
  • E. Philippe Leonelli
    Philippe Leonelli is a French local politician who serves as the mayor of the Mediterranean coastal town of Cavalaire-sur-Mer.
  • 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_69c008d7a9c4819098d647ec47776917 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c067f5bdd481909cf9db595ddb27df completed March 22, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69c63869ef148190816b152f2724de49 completed March 27, 2026, 7:57 a.m.
Created at: March 22, 2026, 4:32 p.m.