Triple

T4500723
Position Surface form Disambiguated ID Type / Status
Subject Dorons of Bozel and Belleville E101210 entity
Predicate hasPart P35 FINISHED
Object Doron de Bozel
Doron de Bozel is a member or branch of the Dorons of Bozel and Belleville family lineage.
 E448172 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: Doron de Bozel | Statement: [Dorons of Bozel and Belleville, hasPart, Doron de Bozel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Doron de Bozel
Context triple: [Dorons of Bozel and Belleville, hasPart, Doron de Bozel]
  • A. Marc Barani
    Marc Barani is a French architect renowned for his refined, context-sensitive public projects and recipient of France’s top national architecture honors.
  • B. Raoul La Roche
    Raoul La Roche was a Swiss banker and prominent art collector known for his patronage of modern architecture and the arts, including commissioning Le Corbusier’s Villa La Roche in Paris.
  • C. Gil Avérous
    Gil Avérous is a French politician who serves as the mayor of the city of Châteauroux.
  • D. Anthony Veiller
    Anthony Veiller was an American screenwriter known for his work on notable mid-20th-century films, including several acclaimed Hollywood dramas and thrillers.
  • E. Bernard Sasia
    Bernard Sasia is a French film editor known for his work on numerous acclaimed European films, including "Monsieur Ibrahim."
  • 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: Doron de Bozel
Triple: [Dorons of Bozel and Belleville, hasPart, Doron de Bozel]
Generated description
Doron de Bozel is a member or branch of the Dorons of Bozel and Belleville family lineage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Doron de Bozel
Target entity description: Doron de Bozel is a member or branch of the Dorons of Bozel and Belleville family lineage.
  • A. Marc Barani
    Marc Barani is a French architect renowned for his refined, context-sensitive public projects and recipient of France’s top national architecture honors.
  • B. Raoul La Roche
    Raoul La Roche was a Swiss banker and prominent art collector known for his patronage of modern architecture and the arts, including commissioning Le Corbusier’s Villa La Roche in Paris.
  • C. Gil Avérous
    Gil Avérous is a French politician who serves as the mayor of the city of Châteauroux.
  • D. Anthony Veiller
    Anthony Veiller was an American screenwriter known for his work on notable mid-20th-century films, including several acclaimed Hollywood dramas and thrillers.
  • E. Bernard Sasia
    Bernard Sasia is a French film editor known for his work on numerous acclaimed European films, including "Monsieur Ibrahim."
  • 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_69bd43d175248190894dc58b5b395c26 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd56c4080c8190bd9580c961acaca8 completed March 20, 2026, 2:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd6f8d498c81908fe1ac5f799f2e1a completed March 20, 2026, 4:02 p.m.
NEDg Description generation batch_69bd71aecafc8190b0815d0308bbcaa9 completed March 20, 2026, 4:11 p.m.
NED2 Entity disambiguation (via description) batch_69bd75f39d788190b9e394050c55f44d completed March 20, 2026, 4:29 p.m.
Created at: March 20, 2026, 1 p.m.