Triple

T12036605
Position Surface form Disambiguated ID Type / Status
Subject William H. Daniels E286555 entity
Predicate notableWork P4 FINISHED
Object Camille E309907 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: Camille | Statement: [William H. Daniels, notableWork, Camille]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Camille
Context triple: [William H. Daniels, notableWork, Camille]
  • A. Camille chosen
    Camille is a classic 1936 romantic drama film starring Greta Garbo as a tragic Parisian courtesan.
  • B. Camille
    Camille is a French given name used for both males and females, historically associated with figures such as the revolutionary journalist Camille Desmoulins.
  • C. Camille Roux
    Camille Roux was an artist associated with the Impressionist movement who participated in the historic Impressionist exhibitions in late 19th-century France.
  • D. Camille Henry
    Camille Henry was a skilled Canadian ice hockey center best known for his prolific scoring with the New York Rangers in the 1950s and 1960s.
  • E. Camille (The Woman in the Green Dress)
    "Camille (The Woman in the Green Dress)" is an 1866 oil painting by Claude Monet portraying his future wife Camille Doncieux in an elegant, fashionable gown, notable for helping establish his early reputation in the Paris art world.
  • 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_69d6ab4669e48190b59246358b0383ab completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90408cbf0819093270c9833ef149a completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49d8a9af881909e28783b0d83ed82 completed May 1, 2026, 12:33 p.m.
Created at: April 8, 2026, 9:47 p.m.