Triple

T10645086
Position Surface form Disambiguated ID Type / Status
Subject Metropolitan Area of Barcelona E250814 entity
Predicate containsMunicipality P852 FINISHED
Object Calella E881435 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: Calella | Statement: [Metropolitan Area of Barcelona, containsMunicipality, Calella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Calella
Context triple: [Metropolitan Area of Barcelona, containsMunicipality, Calella]
  • A. Calella chosen
    Calella is a coastal town and popular tourist destination on the Mediterranean in the Maresme comarca of Catalonia, Spain.
  • B. Calella de Palafrugell
    Calella de Palafrugell is a picturesque traditional fishing village on Spain’s Costa Brava, known for its whitewashed houses, small coves, and scenic Mediterranean coastline.
  • C. Sant Celoni
    Sant Celoni is a town in Catalonia, Spain, located northeast of Barcelona in the Vallès Oriental comarca, known as a local commercial and transport hub between the Montseny and Montnegre natural areas.
  • D. Banyoles
    Banyoles is a town in Catalonia, Spain, best known for its large natural lake and scenic surroundings.
  • E. Benicarló
    Benicarló is a coastal town in the province of Castellón, Spain, known for its Mediterranean beaches, agricultural production (especially artichokes), and historic old quarter.
  • 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_69d6aa5a4c4881908f39be6efe5981e5 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfe120908190ab91c38d57133739 completed April 8, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64b78e7ec819093e5e631197ed295 completed May 2, 2026, 7:07 p.m.
Created at: April 8, 2026, 9:05 p.m.