Triple

T3153360
Position Surface form Disambiguated ID Type / Status
Subject Antonio Canova E65927 entity
Predicate givenName P17 FINISHED
Object Antonio E56351 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: Antonio | Statement: [Antonio Canova, givenName, Antonio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Antonio
Context triple: [Antonio Canova, givenName, Antonio]
  • A. Antonio chosen
    Antonio is a masculine given name of Latin origin, widely used in Italian, Spanish, and Portuguese-speaking cultures.
  • B. Lorenzo
    Lorenzo is a masculine given name of Italian origin, historically borne by notable figures such as the Renaissance humanist Lorenzo Valla.
  • C. Bernardo Morando
    Bernardo Morando was a 16th-century Italian architect best known for designing the Renaissance ideal city of Zamość in Poland.
  • D. Gonzalo
    Gonzalo is a masculine given name of Spanish origin, historically borne by notable figures such as conquistadors, nobles, and literary characters.
  • E. Claudio
    Claudio is a masculine given name of Italian and Spanish origin, commonly used as a variant of the name Claude.
  • 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_69ad8584485081909ed529e890cadc4a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada5c3d6d481908c296e9e09c07f6f completed March 8, 2026, 4:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2250088c48190a226031afda38d87 completed March 12, 2026, 2:29 a.m.
Created at: March 8, 2026, 3:05 p.m.