Triple

T37885270
Position Surface form Disambiguated ID Type / Status
Subject Boccaccio E944977 entity
Predicate character P662 FINISHED
Object Fiametta
Fiametta is a fictional noblewoman created by Giovanni Boccaccio, best known as a central figure and narrator in his early love-themed works.
E2246494 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: Fiametta | Statement: [Boccaccio, character, Fiametta]
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: Fiametta
Triple: [Boccaccio, character, Fiametta]
Generated description
Fiametta is a fictional noblewoman created by Giovanni Boccaccio, best known as a central figure and narrator in his early love-themed works.

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_69f76ef02668819089e7940c4001af5e completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbbd1f99b881908b7af46db083a450 completed May 6, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4104316e1c8190aecb8293ed0d56dd completed June 28, 2026, 11:23 a.m.
NEDg Description generation batch_6a4104c79fb0819084b62acaa5ae7237 completed June 28, 2026, 11:25 a.m.
NED2 Entity disambiguation (via description) batch_6a41059ef42c81909a94722a1563fcd1 completed June 28, 2026, 11:29 a.m.
Created at: May 3, 2026, 4:19 p.m.