Triple

T20010768
Position Surface form Disambiguated ID Type / Status
Subject Paco Tous E494582 entity
Predicate name P16 FINISHED
Object Paco Tous 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: Paco Tous | Statement: [Paco Tous, name, Paco Tous]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paco Tous
Context triple: [Paco Tous, name, Paco Tous]
  • A. Paco Tous chosen
    Paco Tous is a Spanish actor best known internationally for his role as Moscow in the hit television series "La Casa de Papel" ("Money Heist").
  • B. Antonio Suñol
    Antonio Suñol was a 19th-century Californio landowner and politician associated with the early development of the area that later became Sunol, California.
  • C. Ramon Despuig
    Ramon Despuig was a medieval architect known for his work on the Gothic Basilica of Santa Maria del Mar in Barcelona.
  • D. Josep Carner
    Josep Carner was a prominent Catalan poet, writer, and diplomat whose refined, classical style made him one of the leading literary figures of early 20th-century Catalonia.
  • E. Montserrat Ribé
    Montserrat Ribé is a Spanish makeup and special effects artist best known for her work on Guillermo del Toro’s films, including the creature designs in "Pan’s Labyrinth."
  • 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e662362df48190abf16129eea39985 completed April 20, 2026, 5:28 p.m.
Created at: April 11, 2026, 3:33 p.m.