Triple

T36075270
Position Surface form Disambiguated ID Type / Status
Subject Viviane Senna E1043479 entity
Predicate relative P37 FINISHED
Object Leonardo Senna
Leonardo Senna is a member of the prominent Senna family, related to Brazilian businesswoman and philanthropist Viviane Senna and connected to the legacy of Formula 1 legend Ayrton Senna.
E2170026 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: Leonardo Senna | Statement: [Viviane Senna, relative, Leonardo Senna]
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: Leonardo Senna
Triple: [Viviane Senna, relative, Leonardo Senna]
Generated description
Leonardo Senna is a member of the prominent Senna family, related to Brazilian businesswoman and philanthropist Viviane Senna and connected to the legacy of Formula 1 legend Ayrton Senna.

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_69f76e2fd3248190b900d9a492bf5a7a completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b238e3188190a6ae41ea3025bd71 completed May 3, 2026, 8:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38ddf9b75881909559c395ee69a03c completed June 22, 2026, 7:02 a.m.
NEDg Description generation batch_6a38ea9299b881908c77fc1e9aa2e329 completed June 22, 2026, 7:56 a.m.
NED2 Entity disambiguation (via description) batch_6a38eceea1ec8190a5f3a158d37b30ba completed June 22, 2026, 8:06 a.m.
Created at: May 3, 2026, 4:08 p.m.