Triple

T18455598
Position Surface form Disambiguated ID Type / Status
Subject Alberto Fernández E450895 entity
Predicate givenName P17 FINISHED
Object Alberto 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: Alberto | Statement: [Alberto Fernández, givenName, Alberto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alberto
Context triple: [Alberto Fernández, givenName, Alberto]
  • A. Alberto chosen
    Alberto is a masculine given name common in Romance-language countries, derived from the Germanic name Albert and sharing its meaning of "noble" or "bright."
  • B. Roberto
    Roberto is a masculine given name commonly used in Romance-language countries, equivalent to the English name Robert.
  • C. Leonardo Antonelli
    Leonardo Antonelli was an Italian cardinal of the Roman Catholic Church who served as Dean of the College of Cardinals around the turn of the 19th century.
  • D. Renato
    Renato is a masculine given name of Latin origin, commonly used in Italian, Portuguese, and Spanish-speaking countries.
  • E. Hércules Barsotti
    Hércules Barsotti was a Brazilian artist known for his contributions to geometric abstraction and concrete art in the mid-20th century.
  • 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_69d8d38345688190b565eac2e4cd7935 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5264c10408190b2085ade88655c7d completed April 19, 2026, 7 p.m.
Created at: April 10, 2026, 11:31 a.m.