Triple

T2917770
Position Surface form Disambiguated ID Type / Status
Subject Frecce Tricolori E78647 entity
Predicate predecessor P97 FINISHED
Object Getti Tonanti
Getti Tonanti was an early Italian Air Force aerobatic display team that preceded and helped pave the way for the formation of the modern Frecce Tricolori.
 E309860 NE FINISHED

How this triple was built (4 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: Getti Tonanti | Statement: [Frecce Tricolori, predecessor, Getti Tonanti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Getti Tonanti
Context triple: [Frecce Tricolori, predecessor, Getti Tonanti]
  • A. Cominotto
    Cominotto is a small uninhabited islet in the Maltese archipelago, located just off the larger island of Comino.
  • B. Tredozio
    Tredozio is a small Italian municipality in the Emilia-Romagna region, known for its scenic Apennine landscapes and traditional local festivals.
  • C. Saho
    Saho is a Cushitic language spoken primarily by the Saho people in Eritrea and neighboring regions of the Horn of Africa.
  • D. Gigante
    Gigante is a municipality and town located in the Huila Department of southwestern Colombia, known for its agricultural activities and Andean landscapes.
  • E. Logudoro
    Logudoro is a historical-cultural region in northern Sardinia known for its distinctive Sardinian dialect, medieval heritage, and rural landscapes.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Getti Tonanti
Triple: [Frecce Tricolori, predecessor, Getti Tonanti]
Generated description
Getti Tonanti was an early Italian Air Force aerobatic display team that preceded and helped pave the way for the formation of the modern Frecce Tricolori.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Getti Tonanti
Target entity description: Getti Tonanti was an early Italian Air Force aerobatic display team that preceded and helped pave the way for the formation of the modern Frecce Tricolori.
  • A. Cominotto
    Cominotto is a small uninhabited islet in the Maltese archipelago, located just off the larger island of Comino.
  • B. Tredozio
    Tredozio is a small Italian municipality in the Emilia-Romagna region, known for its scenic Apennine landscapes and traditional local festivals.
  • C. Saho
    Saho is a Cushitic language spoken primarily by the Saho people in Eritrea and neighboring regions of the Horn of Africa.
  • D. Gigante
    Gigante is a municipality and town located in the Huila Department of southwestern Colombia, known for its agricultural activities and Andean landscapes.
  • E. Logudoro
    Logudoro is a historical-cultural region in northern Sardinia known for its distinctive Sardinian dialect, medieval heritage, and rural landscapes.
  • F. None of above. chosen

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_69ad8b0c2ad081909ff87050ae542bb9 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad96a41b4c81909d8ace8ab270ed3c completed March 8, 2026, 3:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0562c5b5081908026b3f590b03aca completed March 10, 2026, 5:34 p.m.
NEDg Description generation batch_69b0613dfb048190b08b01837088b9dd completed March 10, 2026, 6:21 p.m.
NED2 Entity disambiguation (via description) batch_69b06514562881909d3b08af898406f7 completed March 10, 2026, 6:38 p.m.
Created at: March 8, 2026, 2:54 p.m.