Triple

T17283494
Position Surface form Disambiguated ID Type / Status
Subject Land of Men E419591 entity
Predicate author P4 FINISHED
Object Antoine de Saint-Exupéry E274271 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: Antoine de Saint-Exupéry | Statement: [Land of Men, author, Antoine de Saint-Exupéry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Antoine de Saint-Exupéry
Context triple: [Land of Men, author, Antoine de Saint-Exupéry]
  • A. Antoine de Saint-Exupéry chosen
    Antoine de Saint-Exupéry was a French aviator and author best known for writing the classic novella "The Little Prince."
  • B. Consuelo de Saint Exupéry
    Consuelo de Saint Exupéry was a Salvadoran-French writer and artist best known as the wife and muse of Antoine de Saint-Exupéry, widely believed to have inspired the character of the rose in "The Little Prince."
  • C. Jean Giono
    Jean Giono was a 20th-century French novelist known for his lyrical, nature-focused prose and works set in rural Provence.
  • D. Maurice Renard
    Maurice Renard was a French writer best known for his early 20th-century science fiction and fantastical novels that explored themes of the uncanny and the supernatural.
  • E. Jules Renard
    Jules Renard was a French writer and diarist best known for his novel "Poil de Carotte" and his incisive, introspective journals.
  • 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_69d886da626481908a14ce7830329a35 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e4332b19f481908acfa88b2f57c5dc completed April 19, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0179535ae08190ac0137d0f8741919 completed May 11, 2026, 6:38 a.m.
Created at: April 10, 2026, 5:40 a.m.