Triple

T3917539
Position Surface form Disambiguated ID Type / Status
Subject Romano Mussolini E88877 entity
Predicate placeOfBirth P1 FINISHED
Object Forlì E78044 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: Forlì | Statement: [Romano Mussolini, placeOfBirth, Forlì]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Forlì
Context triple: [Romano Mussolini, placeOfBirth, Forlì]
  • A. Forlì chosen
    Forlì is a historic city in Italy’s Emilia-Romagna region, known for its medieval architecture, Renaissance art, and role as a provincial capital.
  • B. Gubbio
    Gubbio is a historic medieval town in the Umbria region of central Italy, known for its well-preserved stone architecture and traditional festivals.
  • C. Città di Castello
    Città di Castello is a historic town in the Umbria region of central Italy, known for its medieval architecture, Renaissance art, and location along the upper Tiber River.
  • D. Piacenza
    Piacenza is a historic city in northern Italy known for its strategic location near the Po River, rich medieval and Renaissance architecture, and strong agricultural and industrial traditions.
  • E. Forlì-Cesena
    Forlì-Cesena is a province in Italy’s Emilia-Romagna region, known for its mix of historic towns, agricultural landscapes, and growing industrial and service sectors.
  • 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_69aed955229881909e85e73ffab1d343 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeed5797508190adaddb84575d9bb3 completed March 9, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69befe3ba3848190bcd62dd21229ca67 completed March 21, 2026, 8:23 p.m.
Created at: March 9, 2026, 3:22 p.m.