Triple

T18859787
Position Surface form Disambiguated ID Type / Status
Subject Charles Huet E461278 entity
Predicate nameInNativeLanguage P1435 FINISHED
Object Charles Huet NE NERFINISHED

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: Charles Huet | Statement: [Charles Huet, nameInNativeLanguage, Charles Huet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charles Huet
Context triple: [Charles Huet, nameInNativeLanguage, Charles Huet]
  • A. Charles Huet chosen
    Charles Huet was an artist and mentor known primarily as the teacher of the French painter Jean-Baptiste Huet.
  • B. Charles L’Eplattenier
    Charles L’Eplattenier was a Swiss painter, decorative artist, and influential art teacher whose nature-inspired style helped shape the early artistic development of architect Le Corbusier.
  • C. Charles Lauth
    Charles Lauth was a French chemist and industrialist known for co-founding the École de Physique et Chimie Industrielles de la Ville de Paris, a leading institution in applied science and engineering.
  • D. Charles Lemaresquier
    Charles Lemaresquier was a French architect known for his early 20th-century academic and institutional buildings, continuing the Beaux-Arts tradition in France.
  • E. Charles Huber
    Charles Huber was a local developer and community figure after whom the city of Huber Heights, Ohio, was named.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dcfb7b9c8190854e7b171b98ea2e completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c05fb800819098951ec134a1fa2a completed April 20, 2026, 5:57 a.m.
Created at: April 10, 2026, 11:57 a.m.