Triple

T17331886
Position Surface form Disambiguated ID Type / Status
Subject Nights of Cabiria E420835 entity
Predicate setting P1957 FINISHED
Object Rome NE NERFINISHED

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: Rome | Statement: [Nights of Cabiria, setting, Rome]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rome
Context triple: [Nights of Cabiria, setting, Rome]
  • A. Rome chosen
    Rome is the historic capital of Italy and a major cultural and religious center of the world, renowned for its ancient Roman heritage, art, and architecture.
  • B. Rome
    Rome is a British-American animated television series created by Danger Mouse that blends surreal humor, espionage themes, and distinctive visual style.
  • C. Rome
    Rome is a city in northwestern Georgia, United States, known as a regional center for education, healthcare, and manufacturing in the Appalachian foothills.
  • D. Rome
    Rome is the codename for a generation of AMD EPYC server processors based on the Zen 2 microarchitecture, known for significant improvements in performance and efficiency over its predecessors.
  • E. Roma
    Roma is a historic, centrally located neighborhood in Mexico City known for its tree-lined streets, early 20th-century architecture, and vibrant cultural and culinary scene.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889d3adc881909319f1edb8d2a956 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e439d6870c8190989897aa6beba8ff completed April 19, 2026, 2:11 a.m.
Created at: April 10, 2026, 5:43 a.m.