Triple

T14362126
Position Surface form Disambiguated ID Type / Status
Subject Tivoli plain E356130 entity
Predicate locatedNear P294 FINISHED
Object Tivoli E88741 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: Tivoli | Statement: [Tivoli plain, locatedNear, Tivoli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tivoli
Context triple: [Tivoli plain, locatedNear, Tivoli]
  • A. Tivoli chosen
    Tivoli is an Italian hill town east of Rome renowned for its historic villas and gardens, including Emperor Hadrian’s vast imperial retreat, Hadrian’s Villa.
  • B. Tivoli
    Tivoli is an IBM software brand known for its enterprise systems management and monitoring solutions.
  • C. TivoliVredenburg
    TivoliVredenburg is a large, modern music complex and cultural venue in Utrecht, Netherlands, known for its multiple concert halls and diverse live performances.
  • D. Schmidt Tivoli
    Schmidt Tivoli is a well-known theater and cabaret venue in Hamburg, Germany, famed for its variety shows and musical productions.
  • E. Belvedere
    Belvedere is a premium Polish vodka brand known for its luxury positioning and high-quality production, owned by the French conglomerate LVMH.
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8fabec088190bd8128371b29e958 completed April 14, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd648135188190af86b1b2be2fe0e0 completed May 8, 2026, 4:20 a.m.
Created at: April 10, 2026, 1:15 a.m.