Triple

T16680507
Position Surface form Disambiguated ID Type / Status
Subject Alenia G.222 E405325 entity
Predicate designer P184 FINISHED
Object Aeritalia E405324 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: Aeritalia | Statement: [Alenia G.222, designer, Aeritalia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aeritalia
Context triple: [Alenia G.222, designer, Aeritalia]
  • A. Avio S.p.A.
    Avio S.p.A. is an Italian aerospace company specializing in the design, production, and maintenance of aircraft and space propulsion systems.
  • B. AnsaldoBreda
    AnsaldoBreda is an Italian rolling stock manufacturer known for producing trains, trams, and metro vehicles for rail systems worldwide.
  • C. Avio Aero
    Avio Aero is an Italian aerospace company specializing in the design, production, and maintenance of aircraft engines and gas turbines for civil and military applications.
  • D. Alenia Aeronautica chosen
    Alenia Aeronautica was an Italian aerospace company known for designing and producing military and civilian aircraft before being merged into Leonardo’s aeronautics division.
  • 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 (3 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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37d6f5cf481909e7628bbaa884e5a completed April 18, 2026, 12:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a009d32e7b48190b7dd4660bed4789d completed May 10, 2026, 2:58 p.m.
Created at: April 10, 2026, 5:19 a.m.