Triple

T23043025
Position Surface form Disambiguated ID Type / Status
Subject The White Devil E573792 entity
Predicate settingLocation P40 FINISHED
Object Rome E3694 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: Rome | Statement: [The White Devil, settingLocation, Rome]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rome
Context triple: [The White Devil, settingLocation, Rome]
  • A. Rome
    Rome is a charismatic and confident male stripper and emcee who runs an upscale exotic entertainment venue in the film "Magic Mike XXL."
  • B. 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.
  • C. Rome
    Rome is a British-American animated television series created by Danger Mouse that blends surreal humor, espionage themes, and distinctive visual style.
  • 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. Rome
    Rome is a city in northwestern Georgia, United States, known as a regional center for education, healthcare, and manufacturing in the Appalachian foothills.
  • 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_69e245b9c11481909d06c872214d21af completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18516417081908bf747b20de23a75 completed April 29, 2026, 4:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c159ffb7481909b2987e8aea047ca completed May 19, 2026, 7:47 a.m.
Created at: April 17, 2026, 3:54 p.m.