Triple

T10362149
Position Surface form Disambiguated ID Type / Status
Subject Catalan municipalities E244162 entity
Predicate includeExample P1259 FINISHED
Object 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: Girona | Statement: [Catalan municipalities, includeExample, Girona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Girona
Context triple: [Catalan municipalities, includeExample, 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. Lleida
    Lleida is a historic city in western Catalonia, Spain, known for its medieval Seu Vella cathedral and role as a regional agricultural and commercial center.
  • C. Besalú
    Besalú is a well-preserved medieval town in Catalonia, Spain, renowned for its Romanesque architecture and iconic 12th-century stone bridge.
  • D. Tàrrega
    Tàrrega is a historic town in Catalonia, Spain, known for its cultural festivals and medieval heritage.
  • E. Urgell
    Urgell is a historical comarca in inland Catalonia, known for its agricultural landscapes, medieval towns, and role as part of the broader Urgell region that includes the famous bishopric and valley.
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e962f08c8190a7ac489dc524510d completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69d90d76fd88819086c61c40216a8932 completed April 10, 2026, 2:47 p.m.
Created at: April 6, 2026, 11:59 a.m.