Triple

T25990635
Position Surface form Disambiguated ID Type / Status
Subject Filippo de' Medici E646339 entity
Predicate sibling P363 FINISHED
Object Romola de' Medici
Romola de' Medici was a member of the influential Medici family of Renaissance Florence, connected to the powerful banking and political dynasty that shaped the city's cultural and political life.
E1727911 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: Romola de' Medici | Statement: [Filippo de' Medici, sibling, Romola de' Medici]
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: Romola de' Medici
Triple: [Filippo de' Medici, sibling, Romola de' Medici]
Generated description
Romola de' Medici was a member of the influential Medici family of Renaissance Florence, connected to the powerful banking and political dynasty that shaped the city's cultural and political life.

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_69e77e88cb8481908da31d4a00661f55 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f6054760f08190b41fe4b710d9cc39 completed May 2, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11baf705a48190a7985e4b54585033 completed May 23, 2026, 2:34 p.m.
NEDg Description generation batch_6a11be5eaa64819093fca394daf91d90 completed May 23, 2026, 2:49 p.m.
NED2 Entity disambiguation (via description) batch_6a11bf1dd27c8190b77577de860ac016 completed May 23, 2026, 2:52 p.m.
Created at: April 22, 2026, 8:57 a.m.