Triple

T22743220
Position Surface form Disambiguated ID Type / Status
Subject Friends for Life E562472 entity
Predicate cityAssociatedWith P24465 FINISHED
Object Barcelona NE NERFINISHED

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 | Statement: [Friends for Life, cityAssociatedWith, Barcelona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barcelona
Context triple: [Friends for Life, cityAssociatedWith, 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. Barcelona
    Barcelona is a coastal municipality in the province of Sorsogon in the Bicol Region of the Philippines, known for its historic church and scenic seaside views.
  • C. Barcelona
    Barcelona is a coastal city in northeastern Venezuela that serves as the capital of Anzoátegui state and a major commercial and industrial center in the region.
  • 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. Madrid
    Madrid is a coastal municipality in the Philippine province of Surigao del Sur on the island of Mindanao.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245513a5c81908d5cb471b4fc429d completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17974c3208190ae1d6b05639cc942 completed April 29, 2026, 3:22 a.m.
Created at: April 17, 2026, 3:23 p.m.