Triple

T34377729
Position Surface form Disambiguated ID Type / Status
Subject Duke of Vendôme E882336 entity
Predicate styleOfAddress P536 FINISHED
Object Monseigneur le duc de Vendôme
Monseigneur le duc de Vendôme is a formal French honorific style historically used to address the Duke of Vendôme, a noble title in the French aristocracy.
E2141192 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: Monseigneur le duc de Vendôme | Statement: [Duke of Vendôme, styleOfAddress, Monseigneur le duc de Vendôme]
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: Monseigneur le duc de Vendôme
Triple: [Duke of Vendôme, styleOfAddress, Monseigneur le duc de Vendôme]
Generated description
Monseigneur le duc de Vendôme is a formal French honorific style historically used to address the Duke of Vendôme, a noble title in the French aristocracy.

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_69f349bf5d7481908dd5da4cbdf74047 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f718557a048190ba83c78e00445eae completed May 3, 2026, 9:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a38369441788190b14fb1cc23cafbec completed June 21, 2026, 7:08 p.m.
NEDg Description generation batch_6a3838cf89f48190bc53a2642c4667d2 completed June 21, 2026, 7:17 p.m.
NED2 Entity disambiguation (via description) batch_6a383939ffbc8190abc96d92690e39f4 completed June 21, 2026, 7:19 p.m.
Created at: May 1, 2026, 1:59 a.m.