Triple

T14068098
Position Surface form Disambiguated ID Type / Status
Subject Lycée Saint-Louis E338528 entity
Predicate originalName P65 FINISHED
Object Collège d’Harcourt E65120 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 d’Harcourt | Statement: [Lycée Saint-Louis, originalName, Collège d’Harcourt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Collège d’Harcourt
Context triple: [Lycée Saint-Louis, originalName, Collège d’Harcourt]
  • A. Collège d’Harcourt chosen
    Collège d’Harcourt was a prominent Parisian college of the University of Paris, known for educating notable Enlightenment figures such as Denis Diderot.
  • 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 Sévigné
    Collège Sévigné is a private, progressive secondary school in Paris known for its strong academic tradition and notable alumni.
  • E. 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.
  • 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de568b81f08190a571004261c0e8e4 completed April 14, 2026, 3 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb66aeff8819088239226bbe25fd5 completed May 7, 2026, 3:57 p.m.
Created at: April 9, 2026, 10:21 p.m.