Triple

T5718751
Position Surface form Disambiguated ID Type / Status
Subject Bologna E126086 entity
Predicate hasNickname P39 FINISHED
Object La Rossa E123522 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: La Rossa | Statement: [Bologna, hasNickname, La Rossa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Rossa
Context triple: [Bologna, hasNickname, La Rossa]
  • A. La Rossa chosen
    La Rossa is a well-known nickname for the Italian city of Bologna, reflecting its distinctive red-hued architecture and historical left-wing political leanings.
  • B. Rosanero
    Rosanero is the traditional nickname of Italian football club Palermo FC, referring to the club’s distinctive pink-and-black colors.
  • C. Liberalia
    Liberalia was an ancient Roman religious festival held in honor of the god Liber, associated with fertility, wine, and the coming-of-age of young men.
  • D. Mariana
    Mariana is a neighborhood (barrio) within the city of Dorado, Puerto Rico.
  • E. Mariana
    "Mariana" is a famous 1851 Pre-Raphaelite painting by John Everett Millais depicting a solitary woman in a richly detailed interior, inspired by Shakespeare’s "Measure for Measure" and Tennyson’s poem of the same name.
  • 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_69c0082e3d548190950169847b43043b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024e1ec7c8190a08e1b7954db2a9d completed March 22, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a7db0788190b4a5e7b5d9c94588 completed March 22, 2026, 9:09 p.m.
Created at: March 22, 2026, 3:46 p.m.