Triple

T16380380
Position Surface form Disambiguated ID Type / Status
Subject Micheline Roquebrune E397789 entity
Predicate residence P75 FINISHED
Object Marbella E645251 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: Marbella | Statement: [Micheline Roquebrune, residence, Marbella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marbella
Context triple: [Micheline Roquebrune, residence, Marbella]
  • A. Marbella chosen
    Marbella is a popular resort city on Spain’s Costa del Sol, known for its Mediterranean beaches, luxury marinas, upscale nightlife, and historic old town.
  • B. Benalmádena
    Benalmádena is a coastal resort town on Spain’s Costa del Sol, known for its beaches, marina, and tourist attractions near Málaga.
  • C. Tarifa
    Tarifa is a rural parish within Samborondón Canton in Ecuador’s Guayas Province.
  • D. Tarifa
    Tarifa is a coastal town in southern Spain known as the southernmost point of mainland Europe and a major destination for wind sports like kitesurfing and windsurfing.
  • E. Málaga
    Málaga is a historic port city on Spain’s Costa del Sol, renowned for its Mediterranean beaches, rich Andalusian culture, and as the birthplace of artist Pablo Picasso.
  • 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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e319db5b648190a8fca23518a1fb39 completed April 18, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00758847948190b616cc85e208ee61 completed May 10, 2026, 12:09 p.m.
Created at: April 10, 2026, 5:08 a.m.