Triple

T9290483
Position Surface form Disambiguated ID Type / Status
Subject Castell de Sant Ferran E223502 entity
Predicate region P40 FINISHED
Object Empordà E231220 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: Empordà | Statement: [Castell de Sant Ferran, region, Empordà]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Empordà
Context triple: [Castell de Sant Ferran, region, Empordà]
  • A. Empordà chosen
    Empordà is a historic coastal region in northeastern Catalonia, Spain, known for its medieval villages, Mediterranean landscapes, and strong cultural ties to the artist Salvador Dalí.
  • B. Berguedà
    Berguedà is a mountainous comarca in central Catalonia, Spain, known for its Pyrenean landscapes, rural villages, and natural parks.
  • C. Segarra
    Segarra is a historical inland comarca in Catalonia, Spain, known for its rolling cereal plains, medieval castles, and the town of Cervera as its capital.
  • D. Gandesa
    Gandesa is a historic town in Catalonia, Spain, known for its wine production and role in the Battle of the Ebro during the Spanish Civil War.
  • E. Gandria
    Gandria is a picturesque lakeside village in southern Switzerland known for its historic stone houses, narrow alleyways, and scenic setting on the shores of Lake Lugano.
  • 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_69ca8422ddf881908a3f8f876c9f53aa completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd0865a7108190b807afd259980db2 completed April 1, 2026, 11:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1101359048190b37547d1fedb3bb1 completed April 4, 2026, 1:20 p.m.
Created at: March 30, 2026, 7:35 p.m.