Triple

T5977555
Position Surface form Disambiguated ID Type / Status
Subject José Pancetti E133036 entity
Predicate name P16 FINISHED
Object José Pancetti E133036 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: José Pancetti | Statement: [José Pancetti, name, José Pancetti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: José Pancetti
Context triple: [José Pancetti, name, José Pancetti]
  • A. José Pancetti chosen
    José Pancetti was a prominent Brazilian modernist painter best known for his seascapes and contributions to 20th-century Brazilian art.
  • B. Arsenio
    Arsenio is a masculine given name of Spanish origin, historically borne by several notable figures in Spanish-speaking countries.
  • C. Alfrédo
    Alfrédo is a given name, likely a variant or cognate of "Alfred" or "Alfredo," used as a personal male first name in various languages.
  • D. Eugenio
    Eugenio is a masculine given name of Greek origin, commonly used in Spanish- and Italian-speaking countries.
  • E. Antonio Trashorras
    Antonio Trashorras is a Spanish screenwriter best known for his work in horror cinema, including co-writing Guillermo del Toro’s acclaimed film "The Devil’s Backbone."
  • 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_69c0086f45e8819098f73dd16d45ec9d completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04a3cffb08190a764a404a4ce5812 completed March 22, 2026, 7:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e4184a708190a9e4fe8453463a4b completed March 23, 2026, 6:56 a.m.
Created at: March 22, 2026, 4:04 p.m.