Triple

T13883716
Position Surface form Disambiguated ID Type / Status
Subject Sergio Franchi E333783 entity
Predicate givenName P17 FINISHED
Object Sergio E331003 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: Sergio | Statement: [Sergio Franchi, givenName, Sergio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sergio
Context triple: [Sergio Franchi, givenName, Sergio]
  • A. Sergio chosen
    Sergio is a masculine given name commonly used in Spanish and Italian-speaking countries, derived from the Latin name Sergius.
  • B. Roberto
    Roberto is a masculine given name commonly used in Romance-language countries, equivalent to the English name Robert.
  • C. Jorge
    Jorge is a character portrayed by actor Giancarlo Esposito, known for his nuanced and often intense roles in film and television.
  • D. Jorge
    Jorge is the birth name of Pope Francis, the head of the Roman Catholic Church and the first pope from the Americas.
  • E. Jorge
    Jorge is the given name of the renowned Argentine writer and poet Jorge Luis Borges, a central figure in 20th-century literature.
  • 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_69d81c5dd2d48190b7a5fc1e009de936 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0bea4d248190bcbcea9ea875c5f9 completed April 14, 2026, 9:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd192b5e508190b2d385657f9e358f completed May 7, 2026, 10:58 p.m.
Created at: April 9, 2026, 10:15 p.m.