Triple

T8147582
Position Surface form Disambiguated ID Type / Status
Subject Province of Girona E190252 entity
Predicate contains P35 FINISHED
Object City of Girona E80146 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 Girona | Statement: [Province of Girona, contains, City of Girona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Girona
Context triple: [Province of Girona, contains, City of Girona]
  • A. Girona chosen
    Girona is a historic city in northeastern Catalonia, Spain, known for its well-preserved medieval architecture, walled Old Quarter, and prominent cathedral.
  • B. Tortosa
    Tortosa is a historic city in Catalonia, Spain, known for its medieval architecture and strategic location near the mouth of the Ebro River.
  • 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. Tàrrega
    Tàrrega is a historic town in Catalonia, Spain, known for its cultural festivals and medieval heritage.
  • 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_69ca82be7ba8819087de0147e9292c83 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb447d6b1881908ff3fa25af6b4e80 completed March 31, 2026, 3:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbedc48108190bcf98a82b9625250 completed April 1, 2026, 6:44 a.m.
Created at: March 30, 2026, 5:36 p.m.