Triple

T15086336
Position Surface form Disambiguated ID Type / Status
Subject Granata E360282 entity
Predicate alsoKnownAs P39 FINISHED
Object Il Granata E360282 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: Il Granata | Statement: [Granata, alsoKnownAs, Il Granata]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Il Granata
Context triple: [Granata, alsoKnownAs, Il Granata]
  • A. Granata chosen
    Granata is the traditional nickname of Italian football club Torino F.C., derived from the club’s iconic maroon-colored kit.
  • B. Piove di Sacco
    Piove di Sacco is a town in the Veneto region of northern Italy, historically notable as the birthplace of the 17th-century historian Enrico Caterino Davila.
  • C. Nichelino
    Nichelino is a suburban municipality in the Piedmont region of northwestern Italy, located just south of the city of Turin.
  • D. La Vecchia Signora
    La Vecchia Signora is the famous Italian nickname for Juventus Football Club, one of Italy’s most successful and historic soccer teams.
  • E. La Azul y Blanco
    La Azul y Blanco is the popular nickname for El Salvador’s national football team, referencing the blue and white colors of the country’s flag.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00276d1608190bc310d5b86ecd1d5 completed April 15, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69feae19d0f0819089f330271c9fc6f7 completed May 9, 2026, 3:46 a.m.
Created at: April 10, 2026, 3:03 a.m.