Triple

T9910688
Position Surface form Disambiguated ID Type / Status
Subject Central Catalonia E185132 entity
Predicate containsComarca P33339 FINISHED
Object Solsonès E616316 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: Solsonès | Statement: [Central Catalonia, containsComarca, Solsonès]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Solsonès
Context triple: [Central Catalonia, containsComarca, Solsonès]
  • A. Solsonès chosen
    Solsonès is a rural comarca in central Catalonia, Spain, known for its mountainous landscapes, Romanesque heritage, and the historic town of Solsona.
  • B. Berguedà
    Berguedà is a mountainous comarca in central Catalonia, Spain, known for its Pyrenean landscapes, rural villages, and natural parks.
  • C. Gironella
    Gironella is a small municipality in Catalonia, Spain, known for its historic textile industry and location along the Llobregat River.
  • D. Conca de Barberà
    Conca de Barberà is a comarca (county) in Catalonia, Spain, known for its medieval heritage, wine production, and the presence of the UNESCO-listed Poblet Monastery.
  • E. Vallès Occidental
    Vallès Occidental is a comarca (county) in Catalonia, Spain, known for its industrial cities and proximity to Barcelona within the metropolitan area.
  • 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_69ca8296165881908ca4750701af1f29 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb512a26881908eb72a21ffb1efef completed April 2, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d228a405908190ad63ebd659779ed7 completed April 5, 2026, 9:17 a.m.
Created at: March 30, 2026, 8:41 p.m.