Triple

T37186306
Position Surface form Disambiguated ID Type / Status
Subject Falcone E921329 entity
Predicate hasNotableBearer P458 FINISHED
Object Leonardo Falcone
Leonardo Falcone is an individual notable enough to be recognized as a bearer of the Falcone surname, though specific widely known public achievements or roles are not clearly documented.
E2224078 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 Falcone | Statement: [Falcone, hasNotableBearer, Leonardo Falcone]
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 Falcone
Triple: [Falcone, hasNotableBearer, Leonardo Falcone]
Generated description
Leonardo Falcone is an individual notable enough to be recognized as a bearer of the Falcone surname, though specific widely known public achievements or roles are not clearly documented.

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_69f76ea250bc819083f28d81de25cd0c completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb36185ff88190954ed1fd857c3a7c completed May 6, 2026, 12:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a406cc599888190be1a38a729f85087 completed June 28, 2026, 12:37 a.m.
NEDg Description generation batch_6a406e1111c08190af357e4e318772ba completed June 28, 2026, 12:42 a.m.
NED2 Entity disambiguation (via description) batch_6a406ed77a5c819091554d7e4561aa0b completed June 28, 2026, 12:46 a.m.
Created at: May 3, 2026, 4:15 p.m.