Triple

T10645986
Position Surface form Disambiguated ID Type / Status
Subject UB E250835 entity
Predicate locatedIn P40 FINISHED
Object Barcelona, Spain E9407 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: Barcelona, Spain | Statement: [UB, locatedIn, Barcelona, Spain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barcelona, Spain
Context triple: [UB, locatedIn, Barcelona, Spain]
  • A. Barcelona chosen
    Barcelona is a major Spanish Mediterranean city renowned for its distinctive Catalan culture, Gaudí architecture, and vibrant arts and nightlife scenes.
  • B. El Masnou, Spain
    El Masnou, Spain is a coastal town in the province of Barcelona, Catalonia, known for its Mediterranean beaches and marina.
  • C. Martorell, Spain
    Martorell, Spain is a town in Catalonia best known as a major automotive manufacturing hub and home to SEAT’s main production plant.
  • D. Barcelonès
    Barcelonès is a highly urbanized comarca in Catalonia that includes the city of Barcelona and serves as one of the most densely populated areas in Spain.
  • E. Malaga, Spain
    Malaga, Spain is a historic port city on Spain’s southern Costa del Sol, known for its Mediterranean beaches, rich cultural heritage, and as the birthplace of Pablo Picasso.
  • 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_69e2161018408190bcb64efba0974f8c completed April 17, 2026, 11:14 a.m.
Created at: April 8, 2026, 9:05 p.m.