Triple

T10811785
Position Surface form Disambiguated ID Type / Status
Subject Gwynplaine E255118 entity
Predicate creator P184 FINISHED
Object Victor Hugo E41183 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: Victor Hugo | Statement: [Gwynplaine, creator, Victor Hugo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victor Hugo
Context triple: [Gwynplaine, creator, Victor Hugo]
  • A. Victor Hugo chosen
    Victor Hugo was a 19th-century French novelist, poet, and dramatist, best known for works such as "Les Misérables" and "The Hunchback of Notre-Dame."
  • B. Joseph Léopold Sigisbert Hugo
    Joseph Léopold Sigisbert Hugo was a French general in Napoleon’s army and the father of the famed writer Victor Hugo.
  • C. Place Victor-Hugo
    Place Victor-Hugo is a central public square in the city of Tourcoing, France, known as a local hub of urban life and activity.
  • D. François-Victor Hugo
    François-Victor Hugo was a French writer and renowned translator, best known for his influential French translations of Shakespeare’s works and as the son of author Victor Hugo.
  • E. Charles-Victor Hugo
    Charles-Victor Hugo was a French journalist, photographer, and political activist, best known as one of Victor Hugo’s sons and a defender of press freedom in 19th-century France.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d733b7bfac8190b6ae34144376d6ad completed April 9, 2026, 5:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69de853692f08190914cbeaf1a558730 completed April 14, 2026, 6:19 p.m.
Created at: April 8, 2026, 9:18 p.m.