Triple

T2627709
Position Surface form Disambiguated ID Type / Status
Subject TivoliVredenburg E59158 entity
Predicate namedAfter P63 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: [TivoliVredenburg, namedAfter, Tivoli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tivoli
Context triple: [TivoliVredenburg, namedAfter, 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 an affluent, scenic waterfront city in Marin County, California, known for its views of San Francisco Bay and upscale residential character.
  • 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_69ab4ac558388190962492cd2e1b0ce6 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8b3f72c819085e88f1d74495593 completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69af90a06c4c81908cc4dca65f2190bd completed March 10, 2026, 3:31 a.m.
Created at: March 6, 2026, 9:50 p.m.