Triple

T19147367
Position Surface form Disambiguated ID Type / Status
Subject Abby Rockefeller Mauzé E468713 entity
Predicate spouse P13 FINISHED
Object Jean Mauzé
Jean Mauzé was a French-born banker and investment executive best known as the second husband of philanthropist Abby Rockefeller Mauzé, a member of the prominent Rockefeller family.
E2156237 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: Jean Mauzé | Statement: [Abby Rockefeller Mauzé, spouse, Jean Mauzé]
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: Jean Mauzé
Triple: [Abby Rockefeller Mauzé, spouse, Jean Mauzé]
Generated description
Jean Mauzé was a French-born banker and investment executive best known as the second husband of philanthropist Abby Rockefeller Mauzé, a member of the prominent Rockefeller 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_69d8dd084ff48190ac0f8c46ee722629 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e97a79a48190b243553023bf9081 completed April 20, 2026, 8:53 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3891419b808190a3b951ab1bda560f completed June 22, 2026, 1:34 a.m.
NEDg Description generation batch_6a389278e6948190998204bd8d7bf1bc completed June 22, 2026, 1:40 a.m.
NED2 Entity disambiguation (via description) batch_6a38930372408190a387347aba837518 completed June 22, 2026, 1:42 a.m.
Created at: April 10, 2026, 12:06 p.m.