Triple

T22571217
Position Surface form Disambiguated ID Type / Status
Subject Ursula Bellugi E558078 entity
Predicate familyName P18 FINISHED
Object Bellugi
Bellugi is an Italian surname most notably associated with Ursula Bellugi, a pioneering neuroscientist and linguist known for her work on language and the brain.
 E1542927 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: Bellugi | Statement: [Ursula Bellugi, familyName, Bellugi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bellugi
Context triple: [Ursula Bellugi, familyName, Bellugi]
  • A. Beriev
    Beriev is a Russian aerospace company renowned for designing and manufacturing specialized amphibious and maritime patrol aircraft.
  • B. Aerei
    Aerei is a conceptual artwork series by Italian artist Alighiero Boetti featuring intricate maps of the world overlaid with numerous airplanes in flight.
  • C. Altior
    Altior is a celebrated British National Hunt racehorse renowned for his exceptional unbeaten streak over fences and multiple Grade 1 victories.
  • D. Avion
    Avion is a commune in the Pas-de-Calais department in northern France.
  • E. Potez
    Potez was a French aircraft manufacturer known for producing military and civil airplanes, particularly in the interwar period and during World War II.
  • 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: Bellugi
Triple: [Ursula Bellugi, familyName, Bellugi]
Generated description
Bellugi is an Italian surname most notably associated with Ursula Bellugi, a pioneering neuroscientist and linguist known for her work on language and the brain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bellugi
Target entity description: Bellugi is an Italian surname most notably associated with Ursula Bellugi, a pioneering neuroscientist and linguist known for her work on language and the brain.
  • A. Beriev
    Beriev is a Russian aerospace company renowned for designing and manufacturing specialized amphibious and maritime patrol aircraft.
  • B. Aerei
    Aerei is a conceptual artwork series by Italian artist Alighiero Boetti featuring intricate maps of the world overlaid with numerous airplanes in flight.
  • C. Altior
    Altior is a celebrated British National Hunt racehorse renowned for his exceptional unbeaten streak over fences and multiple Grade 1 victories.
  • D. Avion
    Avion is a commune in the Pas-de-Calais department in northern France.
  • E. Potez
    Potez was a French aircraft manufacturer known for producing military and civil airplanes, particularly in the interwar period and during World War II.
  • 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_69e11e5ae4ac8190b1f503457603d969 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15fae1ed881909430769a0015c39c completed April 29, 2026, 1:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b2d7828988190af945de92c604ac7 completed May 18, 2026, 3:17 p.m.
NEDg Description generation batch_6a0b364801cc81908204a937c1099728 completed May 18, 2026, 3:54 p.m.
NED2 Entity disambiguation (via description) batch_6a0b37998f888190bb53c2429760321a completed May 18, 2026, 4 p.m.
Created at: April 16, 2026, 8:52 p.m.