Triple

T27310124
Position Surface form Disambiguated ID Type / Status
Subject Louis Alexandre de Bourbon E689179 entity
Predicate sibling P363 FINISHED
Object Louis François de Bourbon
Louis François de Bourbon was an 18th-century French prince of the blood from the House of Bourbon, notable as a member of the Condé branch closely connected to the royal family.
E1892814 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: Louis François de Bourbon | Statement: [Louis Alexandre de Bourbon, sibling, Louis François de Bourbon]
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: Louis François de Bourbon
Triple: [Louis Alexandre de Bourbon, sibling, Louis François de Bourbon]
Generated description
Louis François de Bourbon was an 18th-century French prince of the blood from the House of Bourbon, notable as a member of the Condé branch closely connected to the royal family.

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_69ef355b931c8190a63cafaf7bcc008b completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f627b24dd48190a6192153354240ca completed May 2, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2713e9c4848190bedfc575e8eeeea0 completed June 8, 2026, 7:11 p.m.
NEDg Description generation batch_6a2714fad8188190bf86af12ee777b53 completed June 8, 2026, 7:16 p.m.
NED2 Entity disambiguation (via description) batch_6a27198a097c8190aea66eba80acc1d8 completed June 8, 2026, 7:35 p.m.
Created at: April 27, 2026, 11:27 a.m.