Triple

T23124261
Position Surface form Disambiguated ID Type / Status
Subject Pontedera E576981 entity
Predicate hasVehicleBrandAssociated P140875 FINISHED
Object Piaggio NE NERFINISHED

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: Piaggio | Statement: [Pontedera, hasVehicleBrandAssociated, Piaggio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Piaggio
Context triple: [Pontedera, hasVehicleBrandAssociated, Piaggio]
  • A. Piaggio chosen
    Piaggio is an Italian manufacturer best known for producing scooters, motorcycles, and light commercial vehicles, including the iconic Vespa.
  • B. Agusta
    Agusta is an Italian aerospace company known for manufacturing helicopters and aircraft, often under license from other major aviation firms.
  • C. Caproni group
    The Caproni group was an Italian industrial conglomerate best known for its pioneering aircraft manufacturing and aeronautical engineering activities in the early to mid-20th century.
  • D. Caproni
    Caproni was an Italian aircraft manufacturer renowned for producing military and civilian airplanes, particularly during the early to mid-20th century.
  • E. SIAI-Marchetti
    SIAI-Marchetti was an Italian aircraft manufacturer known for producing light military trainers and aerobatic aircraft.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245f6c2e881909a228fdcfeb7c7d3 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18e5299c08190a578102cf2ff7080 completed April 29, 2026, 4:51 a.m.
Created at: April 17, 2026, 3:59 p.m.