Triple

T10689746
Position Surface form Disambiguated ID Type / Status
Subject Blanche Hoschedé E251977 entity
Predicate spouse P13 FINISHED
Object Jean Monet E727255 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: Jean Monet | Statement: [Blanche Hoschedé, spouse, Jean Monet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jean Monet
Context triple: [Blanche Hoschedé, spouse, Jean Monet]
  • A. Jean Monet chosen
    Jean Monet was the son of French Impressionist painter Claude Monet and a frequent subject in his father's early paintings.
  • B. Michel Monet
    Michel Monet was a French painter and the younger son of Impressionist master Claude Monet, known for preserving and promoting his father's artistic legacy.
  • C. Tiburce Morisot
    Tiburce Morisot was a member of the Morisot family, related to the 19th-century French painter Edma Morisot.
  • D. Camille Monet
    Camille Monet was the first wife and frequent model of French Impressionist painter Claude Monet, appearing in many of his early works.
  • E. Theodore Robinson
    Theodore Robinson was an American Impressionist painter known for his close association with Claude Monet and his influential depictions of Giverny and rural life.
  • 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_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fd1c0f0081908a6869ee756ec789 completed April 9, 2026, 1:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69d988a59d6c8190a0e170acfb3af6da completed April 10, 2026, 11:32 p.m.
Created at: April 8, 2026, 9:11 p.m.