Triple

T21623936
Position Surface form Disambiguated ID Type / Status
Subject Mathurin Cordier E533647 entity
Predicate taughtAt P1203 FINISHED
Object Collège de la Marche NE NERFINISHED

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: Collège de la Marche | Statement: [Mathurin Cordier, taughtAt, Collège de la Marche]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Collège de la Marche
Context triple: [Mathurin Cordier, taughtAt, Collège de la Marche]
  • A. Collège de la Marche chosen
    Collège de la Marche was a notable Parisian college of the University of Paris, known for educating prominent Enlightenment-era scholars and intellectuals.
  • B. Collège de Coqueret
    Collège de Coqueret was a notable 16th-century Parisian humanist college renowned for educating prominent French Renaissance figures such as poet Pierre de Ronsard.
  • C. Collège de Montaigu
    Collège de Montaigu was a prominent medieval college of the University of Paris known for educating influential theologians and humanist scholars.
  • D. Collège d’Harcourt
    Collège d’Harcourt was a prominent Parisian college of the University of Paris, known for educating notable Enlightenment figures such as Denis Diderot.
  • E. Collège Sévigné
    Collège Sévigné is a private, progressive secondary school in Paris known for its strong academic tradition and notable alumni.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c464fba881908d0ff2ac80511ce1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef521125f481909ccfc95d884976e2 completed April 27, 2026, 12:09 p.m.
Created at: April 16, 2026, 6:34 p.m.