Triple

T2428675
Position Surface form Disambiguated ID Type / Status
Subject Park Güell E52790 entity
Predicate owner P347 FINISHED
Object City of Barcelona 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: City of Barcelona | Statement: [Park Güell, owner, City of Barcelona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Barcelona
Context triple: [Park Güell, owner, City of Barcelona]
  • 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. 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.
  • C. Sant Joan Despí
    Sant Joan Despí is a municipality in the Baix Llobregat comarca near Barcelona, Spain, known for its modernist architecture and role as a residential and industrial suburb of the Catalan capital.
  • D. Girona
    Girona is a historic city in northeastern Catalonia, Spain, known for its well-preserved medieval architecture, walled Old Quarter, and prominent cathedral.
  • E. Ciutat Vella
    Ciutat Vella is Barcelona’s historic city center, known for its medieval streets, Gothic architecture, and major cultural landmarks.
  • 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_69ab4959bcc0819083246f9fb10439e3 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc99e1b548190aca9a0ba72a9b0f7 completed March 7, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98a342508190b30766327f298bf9 completed March 10, 2026, 4:05 a.m.
Created at: March 6, 2026, 9:43 p.m.