Triple

T18418378
Position Surface form Disambiguated ID Type / Status
Subject Gianinna Maradona E441953 entity
Predicate givenName P17 FINISHED
Object Gianinna
Gianinna is an Argentine public figure best known as the daughter of legendary footballer Diego Maradona.
 E1323798 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: Gianinna | Statement: [Gianinna Maradona, givenName, Gianinna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gianinna
Context triple: [Gianinna Maradona, givenName, Gianinna]
  • A. Giovannina
    Giovannina is an Italian feminine given name, typically used as a diminutive or affectionate form of Giovanna.
  • B. Lodoletta
    Lodoletta is an opera in three acts by Italian composer Pietro Mascagni, known for its verismo style and tragic love story.
  • C. Guglielma
    Guglielma is an Italian feminine given name, serving as the female variant of Guglielmo (William).
  • D. Gianetta
    Gianetta is one of the lively, romantic young Venetian girls in Gilbert and Sullivan’s comic opera "The Gondoliers," who becomes entangled in the opera’s mistaken-identity royal plot.
  • E. Lorenza
    Lorenza is a Chilean actress and model best known for her roles in films like "Knock Knock" and "Once Upon a Time in Hollywood."
  • 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: Gianinna
Triple: [Gianinna Maradona, givenName, Gianinna]
Generated description
Gianinna is an Argentine public figure best known as the daughter of legendary footballer Diego Maradona.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gianinna
Target entity description: Gianinna is an Argentine public figure best known as the daughter of legendary footballer Diego Maradona.
  • A. Giovannina
    Giovannina is an Italian feminine given name, typically used as a diminutive or affectionate form of Giovanna.
  • B. Lodoletta
    Lodoletta is an opera in three acts by Italian composer Pietro Mascagni, known for its verismo style and tragic love story.
  • C. Guglielma
    Guglielma is an Italian feminine given name, serving as the female variant of Guglielmo (William).
  • D. Gianetta
    Gianetta is one of the lively, romantic young Venetian girls in Gilbert and Sullivan’s comic opera "The Gondoliers," who becomes entangled in the opera’s mistaken-identity royal plot.
  • E. Lorenza
    Lorenza is a Chilean actress and model best known for her roles in films like "Knock Knock" and "Once Upon a Time in Hollywood."
  • 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_69d8b9eb8a508190a942fd75ebd8b1dc completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e51a2a0fb08190b409ed200a9d86a6 completed April 19, 2026, 6:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03f0a633448190880b67ffe4f4e55b completed May 13, 2026, 3:31 a.m.
NEDg Description generation batch_6a03f21c622c81909f34f0d3da0c4491 completed May 13, 2026, 3:38 a.m.
NED2 Entity disambiguation (via description) batch_6a03f356e48c81908d74414b736303a4 completed May 13, 2026, 3:43 a.m.
Created at: April 10, 2026, 10:47 a.m.