Triple

T10946118
Position Surface form Disambiguated ID Type / Status
Subject Cesena E258600 entity
Predicate localDialect P1762 FINISHED
Object Romagnol E33911 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: Romagnol | Statement: [Cesena, localDialect, Romagnol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Romagnol
Context triple: [Cesena, localDialect, Romagnol]
  • A. Emilian-Romagnol chosen
    Emilian-Romagnol is a Romance language variety spoken primarily in Italy’s Emilia-Romagna region, known for its distinct phonology and vocabulary compared to standard Italian.
  • B. Brescian
    Brescian is a variety of the Lombard language traditionally spoken in and around the city of Brescia in northern Italy.
  • C. Piacentini
    Piacentini are the inhabitants or natives of the Italian city of Piacenza, located in the Emilia-Romagna region.
  • D. Ferrarese
    Ferrarese is a regional variety of the Emilian-Romagnol language spoken in and around the city of Ferrara in northern Italy.
  • E. Piemontese
    Piemontese is a Romance language spoken primarily in Italy’s Piedmont region, distinct from standard Italian and recognized for its own rich literary and cultural tradition.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770e9a89081908979efd1d9e6af66 completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23c3c885081908edcece772b2e759 completed April 17, 2026, 1:57 p.m.
Created at: April 8, 2026, 9:23 p.m.