Triple

T18160576
Position Surface form Disambiguated ID Type / Status
Subject Marcellin Desboutin E434747 entity
Predicate familyName P18 FINISHED
Object Desboutin
Desboutin is a French surname most notably associated with the 19th-century painter and printmaker Marcellin Desboutin.
 E1309091 NE FINISHED

How this triple was built (4 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: Desboutin | Statement: [Marcellin Desboutin, familyName, Desboutin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Desboutin
Context triple: [Marcellin Desboutin, familyName, Desboutin]
  • A. Breuillet
    Breuillet is a commune in the Essonne department in the Île-de-France region of northern France.
  • B. Peney-Dessous
    Peney-Dessous is a small village in the municipality of Satigny in the canton of Geneva, Switzerland.
  • C. Béraud
    Béraud is a French surname most notably associated with the 19th-century painter Jean Béraud, renowned for his vivid depictions of Parisian life during the Belle Époque.
  • D. Boucicaut
    Boucicaut is a station on the Paris Métro serving the 15th arrondissement of Paris.
  • E. Bollaert
    Bollaert is the commonly used nickname for Stade Bollaert-Delelis, the historic football stadium in Lens, France.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Desboutin
Triple: [Marcellin Desboutin, familyName, Desboutin]
Generated description
Desboutin is a French surname most notably associated with the 19th-century painter and printmaker Marcellin Desboutin.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Desboutin
Target entity description: Desboutin is a French surname most notably associated with the 19th-century painter and printmaker Marcellin Desboutin.
  • A. Breuillet
    Breuillet is a commune in the Essonne department in the Île-de-France region of northern France.
  • B. Peney-Dessous
    Peney-Dessous is a small village in the municipality of Satigny in the canton of Geneva, Switzerland.
  • C. Béraud
    Béraud is a French surname most notably associated with the 19th-century painter Jean Béraud, renowned for his vivid depictions of Parisian life during the Belle Époque.
  • D. Boucicaut
    Boucicaut is a station on the Paris Métro serving the 15th arrondissement of Paris.
  • E. Bollaert
    Bollaert is the commonly used nickname for Stade Bollaert-Delelis, the historic football stadium in Lens, France.
  • F. None of above. chosen

Provenance (5 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_69d8b90b7a188190b3fc7b8d4a6cd20a completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dec21e6081909070491f679c873c completed April 19, 2026, 1:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a038fbeb73c81909fd3ce75e4b37ae5 completed May 12, 2026, 8:38 p.m.
NEDg Description generation batch_6a039064e8708190b176eaa15eab97e6 completed May 12, 2026, 8:41 p.m.
NED2 Entity disambiguation (via description) batch_6a039126d58c8190882d3171bf388a10 completed May 12, 2026, 8:44 p.m.
Created at: April 10, 2026, 10:30 a.m.