Triple

T5686603
Position Surface form Disambiguated ID Type / Status
Subject François Blondel E125328 entity
Predicate educatedAt P5 FINISHED
Object Collège de Clermont E110646 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: Collège de Clermont | Statement: [François Blondel, educatedAt, Collège de Clermont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Collège de Clermont
Context triple: [François Blondel, educatedAt, Collège de Clermont]
  • A. Collège de Clermont chosen
    Collège de Clermont was the historic Parisian Jesuit college that later became the prestigious Lycée Louis-le-Grand.
  • B. Collège de la Marche
    Collège de la Marche was a notable Parisian college of the University of Paris, known for educating prominent Enlightenment-era scholars and intellectuals.
  • 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 de Vendôme
    Collège de Vendôme is a historic French educational institution in Vendôme, notable for having educated the renowned writer Honoré de Balzac.
  • E. 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.
  • 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_69c0082a884c8190a79001bae658941f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023bbfb988190bb61c7d183660d5d completed March 22, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a40b3808190bc57fde5990ac04e completed March 22, 2026, 9:08 p.m.
Created at: March 22, 2026, 3:44 p.m.