Triple

T20080387
Position Surface form Disambiguated ID Type / Status
Subject Úrsula Corberó E499984 entity
Predicate familyName P18 FINISHED
Object Corberó 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: Corberó | Statement: [Úrsula Corberó, familyName, Corberó]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Corberó
Context triple: [Úrsula Corberó, familyName, Corberó]
  • A. Corberó chosen
    Corberó is a Spanish surname most notably associated with actress Úrsula Corberó, known internationally for her role in the series "Money Heist" (La Casa de Papel).
  • B. Camarasa
    Camarasa is a municipality in the province of Lleida, Catalonia, Spain, known for its reservoir and scenic location in the Noguera region.
  • C. Gironella
    Gironella is a small municipality in Catalonia, Spain, known for its historic textile industry and location along the Llobregat River.
  • D. Tordera
    Tordera is a municipality in the Maresme comarca of Catalonia, Spain, known for its rural landscapes and proximity to the Costa Brava.
  • E. La Garriga
    La Garriga is a municipality in Catalonia, Spain, known for its modernist architecture, thermal baths, and location at the foot of the Montseny massif.
  • 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66557c19c8190b511857490bbd423 completed April 20, 2026, 5:41 p.m.
Created at: April 11, 2026, 3:41 p.m.