Triple

T5991113
Position Surface form Disambiguated ID Type / Status
Subject Alessandra Mussolini E133351 entity
Predicate givenName P17 FINISHED
Object Alessandra
Alessandra is an Italian politician, former actress, and granddaughter of Benito Mussolini.
 E562260 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: Alessandra | Statement: [Alessandra Mussolini, givenName, Alessandra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Alessandra
Context triple: [Alessandra Mussolini, givenName, Alessandra]
  • A. Romina
    Romina is an Italian-American actress and singer best known as half of the pop duo Al Bano & Romina Power.
  • B. Luciana
    Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
  • C. Melina
    Melina is a key resistance fighter and love interest in the science fiction film "Total Recall," known for aiding the protagonist in his struggle against a corrupt Martian regime.
  • D. Daniela
    Daniela is a feminine given name commonly used in many languages, often as the female form of Daniel.
  • E. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • 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: Alessandra
Triple: [Alessandra Mussolini, givenName, Alessandra]
Generated description
Alessandra is an Italian politician, former actress, and granddaughter of Benito Mussolini.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Alessandra
Target entity description: Alessandra is an Italian politician, former actress, and granddaughter of Benito Mussolini.
  • A. Romina
    Romina is an Italian-American actress and singer best known as half of the pop duo Al Bano & Romina Power.
  • B. Luciana
    Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
  • C. Melina
    Melina is a key resistance fighter and love interest in the science fiction film "Total Recall," known for aiding the protagonist in his struggle against a corrupt Martian regime.
  • D. Daniela
    Daniela is a feminine given name commonly used in many languages, often as the female form of Daniel.
  • E. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • 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_69c0087010d081908bb8142342d63330 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04dc8ab648190beb1bc141796894e completed March 22, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c10861c0bc8190b6290d7363f4264a completed March 23, 2026, 9:31 a.m.
NEDg Description generation batch_69c10c44b6408190be8bc1d96e0db2e4 completed March 23, 2026, 9:47 a.m.
NED2 Entity disambiguation (via description) batch_69c10cd7c1c8819085ec8bee7f42afc4 completed March 23, 2026, 9:50 a.m.
Created at: March 22, 2026, 4:05 p.m.