Triple

T31357136
Position Surface form Disambiguated ID Type / Status
Subject Tamburini E799765 entity
Predicate hasNotableBearer P458 FINISHED
Object Massimo Tamburini
Massimo Tamburini was an influential Italian motorcycle designer best known for creating iconic sportbikes for Ducati and MV Agusta, including the Ducati 916 and MV Agusta F4.
E1969736 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: Massimo Tamburini | Statement: [Tamburini, hasNotableBearer, Massimo Tamburini]
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: Massimo Tamburini
Triple: [Tamburini, hasNotableBearer, Massimo Tamburini]
Generated description
Massimo Tamburini was an influential Italian motorcycle designer best known for creating iconic sportbikes for Ducati and MV Agusta, including the Ducati 916 and MV Agusta F4.

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_69f224e5e9bc8190a16339328897c4f8 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69f48370481909e9d58d2cbff9466 completed May 3, 2026, 1:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b561d51f08190bd358ea9ea13a2a1 completed June 12, 2026, 12:43 a.m.
NEDg Description generation batch_6a2b5721f7d881908b69012200480bba completed June 12, 2026, 12:47 a.m.
NED2 Entity disambiguation (via description) batch_6a2b710696208190a3b8ab6972fdf69b completed June 12, 2026, 2:37 a.m.
Created at: April 29, 2026, 9:17 p.m.