Triple

T19455661
Position Surface form Disambiguated ID Type / Status
Subject Marbella E486725 entity
Predicate hasPart P35 FINISHED
Object Puerto Banús 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: Puerto Banús | Statement: [Marbella, hasPart, Puerto Banús]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Puerto Banús
Context triple: [Marbella, hasPart, Puerto Banús]
  • A. Puerto Banús chosen
    Puerto Banús is a luxury marina and upscale resort area near Marbella in southern Spain, famed for its high-end boutiques, nightlife, and yacht-filled harbor.
  • B. Malecón
    Malecón is a famous seaside promenade in Puerto Vallarta known for its ocean views, public art, and vibrant social atmosphere.
  • C. Malecón
    Malecón is a famous seaside promenade and seawall in Havana, Cuba, known for its ocean views, social life, and historic architecture.
  • D. Bay of Zea
    The Bay of Zea is a natural harbor in Piraeus, Greece, historically used as an ancient naval port and later as a venue for early modern Olympic events.
  • E. Vedado
    Vedado is a prominent residential and cultural neighborhood in Havana, Cuba, known for its modernist architecture, nightlife, and proximity to the Malecón waterfront.
  • 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_69d8e8d86d608190bd199a98d0297f27 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e633c2b1108190b492ca23487b91f8 completed April 20, 2026, 2:10 p.m.
Created at: April 10, 2026, 1:38 p.m.