Triple

T23309584
Position Surface form Disambiguated ID Type / Status
Subject Autopista AP-7 E590544 entity
Predicate passesNear P416 FINISHED
Object Marbella 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: Marbella | Statement: [Autopista AP-7, passesNear, Marbella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marbella
Context triple: [Autopista AP-7, passesNear, 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 (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_69e25d1d32188190948eb76909d1dcc3 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f19729f7a4819092a1d24415b3df7a completed April 29, 2026, 5:29 a.m.
Created at: April 17, 2026, 5:05 p.m.