Triple

T24797729
Position Surface form Disambiguated ID Type / Status
Subject Anne Jules de Noailles E620433 entity
Predicate mother P120 FINISHED
Object Louise Boyer
Louise Boyer was a French noblewoman of the 17th century, best known as the mother of Marshal Anne Jules de Noailles and a member of the influential Noailles family circle at the court of Louis XIV.
E1657216 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: Louise Boyer | Statement: [Anne Jules de Noailles, mother, Louise Boyer]
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: Louise Boyer
Triple: [Anne Jules de Noailles, mother, Louise Boyer]
Generated description
Louise Boyer was a French noblewoman of the 17th century, best known as the mother of Marshal Anne Jules de Noailles and a member of the influential Noailles family circle at the court of Louis XIV.

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_69e2fabe77c8819085f7ce6486248139 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f412a7d950819099f1a7298c138d30 completed May 1, 2026, 2:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10330b84288190a96eaef09b2d1e42 completed May 22, 2026, 10:42 a.m.
NEDg Description generation batch_6a10341e764c819083c10e4d151da1c6 completed May 22, 2026, 10:46 a.m.
NED2 Entity disambiguation (via description) batch_6a1034cf890881908bd25523cdb83586 completed May 22, 2026, 10:49 a.m.
Created at: April 18, 2026, 4:48 a.m.