Triple

T15562437
Position Surface form Disambiguated ID Type / Status
Subject Federica Mogherini E371031 entity
Predicate givenName P17 FINISHED
Object Federica
Federica is an Italian given name most notably borne by Federica Mogherini, a prominent Italian politician and former EU High Representative for Foreign Affairs and Security Policy.
E1163521 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: Federica | Statement: [Federica Mogherini, givenName, Federica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Federica
Context triple: [Federica Mogherini, givenName, Federica]
  • A. Nicoletta
    Nicoletta is an Italian given name commonly used for women, derived from the name Nicola.
  • B. Letizia
    Letizia is a feminine given name of Italian origin, famously borne by Maria Letizia Ramolino, the mother of Napoleon Bonaparte.
  • C. Lelia
    Lelia is the given name of A'Lelia Walker, an influential African-American businesswoman and patron of the arts during the Harlem Renaissance.
  • D. Giuliana
    Giuliana is an Italian feminine given name, commonly considered the female form of Giuliano.
  • E. Alessandra
    Alessandra is an Italian politician, former actress, and granddaughter of Benito Mussolini.
  • 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: Federica
Triple: [Federica Mogherini, givenName, Federica]
Generated description
Federica is an Italian given name most notably borne by Federica Mogherini, a prominent Italian politician and former EU High Representative for Foreign Affairs and Security Policy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Federica
Target entity description: Federica is an Italian given name most notably borne by Federica Mogherini, a prominent Italian politician and former EU High Representative for Foreign Affairs and Security Policy.
  • A. Nicoletta
    Nicoletta is an Italian given name commonly used for women, derived from the name Nicola.
  • B. Letizia
    Letizia is a feminine given name of Italian origin, famously borne by Maria Letizia Ramolino, the mother of Napoleon Bonaparte.
  • C. Lelia
    Lelia is the given name of A'Lelia Walker, an influential African-American businesswoman and patron of the arts during the Harlem Renaissance.
  • D. Giuliana
    Giuliana is an Italian feminine given name, commonly considered the female form of Giuliano.
  • E. Alessandra
    Alessandra is an Italian politician, former actress, and granddaughter of Benito Mussolini.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ddc66448190948280fb0c8d390c completed April 16, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff456821988190971539b683f6c656 completed May 9, 2026, 2:32 p.m.
NEDg Description generation batch_69ff46f44b2c81909f65f0ab455c6549 completed May 9, 2026, 2:38 p.m.
NED2 Entity disambiguation (via description) batch_69ff477a63b48190a453cf669dfda228 completed May 9, 2026, 2:40 p.m.
Created at: April 10, 2026, 4:09 a.m.