Triple

T7763158
Position Surface form Disambiguated ID Type / Status
Subject Arona E176074 entity
Predicate hasUrbanArea P316 FINISHED
Object Los Cristianos E687639 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: Los Cristianos | Statement: [Arona, hasUrbanArea, Los Cristianos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Los Cristianos
Context triple: [Arona, hasUrbanArea, Los Cristianos]
  • A. Los Cristianos chosen
    Los Cristianos is a popular coastal resort town on the south coast of Tenerife in Spain’s Canary Islands, known for its beaches, harbor, and vibrant tourist amenities.
  • B. Santamaría
    Santamaría is a Spanish-language surname borne by various notable figures in Latin American history and culture.
  • C. Les Corts
    Les Corts is a district in the western part of Barcelona, Spain, known for its residential character and for hosting the FC Barcelona stadium, Camp Nou.
  • D. El Rosal
    El Rosal is a municipality in the Cundinamarca Department of Colombia, located in the Bogotá savanna near the capital city.
  • E. Badalona
    Badalona is a coastal city in Catalonia, Spain, known as part of the Barcelona metropolitan area and for its strong basketball tradition.
  • 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_69c69962923c8190ac74d28b4f9fe0a0 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c704061d1881909b5b42bb93d2b8a7 completed March 27, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8d6c8276c8190bdc3efc2a6175610 completed March 29, 2026, 7:37 a.m.
Created at: March 27, 2026, 4:09 p.m.