Triple

T3467914
Position Surface form Disambiguated ID Type / Status
Subject Mole Antonelliana E73181 entity
Predicate namedAfter P63 FINISHED
Object Alessandro Antonelli E525173 NE FINISHED

How this triple was built (2 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: Alessandro Antonelli | Statement: [Mole Antonelliana, namedAfter, Alessandro Antonelli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alessandro Antonelli
Context triple: [Mole Antonelliana, namedAfter, Alessandro Antonelli]
  • A. Alessandro Antonelli chosen
    Alessandro Antonelli was a 19th-century Italian architect best known for designing Turin’s iconic Mole Antonelliana.
  • B. Franco Antonicelli
    Franco Antonicelli was an Italian intellectual, publisher, and anti-fascist activist known for promoting important 20th-century literature and political thought.
  • C. Filippo Barigioni
    Filippo Barigioni was an Italian Baroque architect and sculptor active in Rome in the early 18th century, known for his work on churches, fountains, and urban spaces.
  • D. Stefano Arnaldi
    Stefano Arnaldi is a composer best known for creating the musical score for the film "Tea with Mussolini."
  • E. Federico Bruni
    Federico Bruni, better known as Fyodor Bruni, was a 19th-century Italian-Russian painter renowned for his large-scale historical and religious works in the academic style.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad85b224d481908ff8be51338d24ff completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbb11ec5881908347bf92883a25ee completed March 8, 2026, 6:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf88d99da08190996996079b947498 completed March 22, 2026, 6:14 a.m.
Created at: March 8, 2026, 3:17 p.m.