Triple

T25867213
Position Surface form Disambiguated ID Type / Status
Subject Bianca de' Medici E651649 entity
Predicate spouse P13 FINISHED
Object Guglielmo de' Pazzi
Guglielmo de' Pazzi was a 15th-century Florentine nobleman of the powerful Pazzi family, notably linked to the Medici through his marriage to Bianca de' Medici during the turbulent era of the Pazzi Conspiracy.
E1699252 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: Guglielmo de' Pazzi | Statement: [Bianca de' Medici, spouse, Guglielmo de' Pazzi]
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: Guglielmo de' Pazzi
Triple: [Bianca de' Medici, spouse, Guglielmo de' Pazzi]
Generated description
Guglielmo de' Pazzi was a 15th-century Florentine nobleman of the powerful Pazzi family, notably linked to the Medici through his marriage to Bianca de' Medici during the turbulent era of the Pazzi Conspiracy.

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_69e7ab3a199c81909227cb964cacfe24 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f602d9b5c8819093aebab7bb20044d completed May 2, 2026, 1:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10da43d304819081b074f1e9ee0cb7 completed May 22, 2026, 10:35 p.m.
NEDg Description generation batch_6a10df335ba08190817c6f32bfd16055 completed May 22, 2026, 10:56 p.m.
NED2 Entity disambiguation (via description) batch_6a10e473d0348190bd255b2acdd624bf completed May 22, 2026, 11:19 p.m.
Created at: April 22, 2026, 8:07 a.m.