Triple

T2345917
Position Surface form Disambiguated ID Type / Status
Subject Camille Doncieux E45129 entity
Predicate hasChild P369 FINISHED
Object Jean Monet E276239 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: [Camille Doncieux, hasChild, Jean Monet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jean Monet
Context triple: [Camille Doncieux, hasChild, Jean Monet]
  • A. Michel Monet chosen
    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.
  • B. Camille Monet
    Camille Monet was the first wife and frequent model of French Impressionist painter Claude Monet, appearing in many of his early works.
  • C. Blanche Hoschedé-Monet
    Blanche Hoschedé-Monet was a French Impressionist painter and the stepdaughter and devoted assistant of Claude Monet, known for continuing his artistic legacy.
  • D. Henri Le Sidaner
    Henri Le Sidaner was a French post-impressionist painter known for his intimate, atmospheric scenes of quiet towns, gardens, and twilight interiors rendered in soft, luminous tones.
  • E. Claude Monet
    Claude Monet was a pioneering French Impressionist painter renowned for his luminous landscapes and series capturing changing light and atmosphere, such as his water lilies and haystacks.
  • 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_69a88917935081909b755dbf38e81024 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abc6c7cb9481909405aeb503f804ae completed March 7, 2026, 6:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69afbbaafe788190b0bbe84f26536cf0 completed March 10, 2026, 6:35 a.m.
Created at: March 4, 2026, 7:52 p.m.