Triple

T11554908
Position Surface form Disambiguated ID Type / Status
Subject Province of Alicante E273993 entity
Predicate contains P35 FINISHED
Object Benidorm E224969 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: Benidorm | Statement: [Province of Alicante, contains, Benidorm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Benidorm
Context triple: [Province of Alicante, contains, Benidorm]
  • A. Benidorm chosen
    Benidorm is a major Spanish Mediterranean resort city famous for its skyscraper-lined beaches, vibrant nightlife, and mass tourism.
  • B. Denia
    Denia is a coastal city on Spain’s Costa Blanca known for its historic castle, Mediterranean beaches, and vibrant port.
  • C. Lloret de Mar
    Lloret de Mar is a popular Mediterranean coastal resort town on Spain’s Costa Brava, known for its beaches, nightlife, and tourism.
  • D. Marbella
    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.
  • E. Cala d'Or
    Cala d'Or is a popular resort town on Mallorca’s southeastern coast, known for its sheltered coves, sandy beaches, and whitewashed, Ibizan-style architecture.
  • 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_69d6aae4dfa48190a3ab0b19a159a3c5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88a86be308190973fea5d7db8ba9d completed April 10, 2026, 5:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef12f0661081909c31de2c2cd304e3 completed April 27, 2026, 7:40 a.m.
Created at: April 8, 2026, 9:37 p.m.