Triple

T3329606
Position Surface form Disambiguated ID Type / Status
Subject Antonio Davis E70001 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 Davis, givenName, Antonio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Antonio
Context triple: [Antonio Davis, givenName, Antonio]
  • A. Antonio chosen
    Antonio is a masculine given name of Latin origin, widely used in Italian, Spanish, and Portuguese-speaking cultures.
  • B. Antonio Vandone di Cortemilia
    Antonio Vandone di Cortemilia was an Italian architect known for designing the Mogadishu Cathedral in Somalia during the colonial era.
  • C. Lorenzo
    Lorenzo is a masculine given name of Italian origin, historically borne by notable figures such as the Renaissance humanist Lorenzo Valla.
  • D. Bernardo Morando
    Bernardo Morando was a 16th-century Italian architect best known for designing the Renaissance ideal city of Zamość in Poland.
  • E. Ignazio
    Ignazio is an Italian given name, cognate to Ignacy and typically associated with the Latin-rooted names Ignatius and Ignacio.
  • 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_69ad85a24f208190bcf83131bfed3521 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb171ee0881908642504ab0ac8329 completed March 8, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a810e2c8190bfc206bdeb1ac5b8 completed March 12, 2026, 7:56 p.m.
Created at: March 8, 2026, 3:12 p.m.