Triple

T20405685
Position Surface form Disambiguated ID Type / Status
Subject Octavio E500461 entity
Predicate hasVariant P455 FINISHED
Object Ottavio 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: Ottavio | Statement: [Octavio, hasVariant, Ottavio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ottavio
Context triple: [Octavio, hasVariant, Ottavio]
  • A. Ottavio chosen
    Ottavio is an Italian given name historically borne by notable figures such as Renaissance nobles and churchmen, including members of the Farnese family.
  • B. Ludovico
    Ludovico is an Italian given name, historically borne by various notable figures in art, music, and nobility.
  • C. Pietro Antonio
    Pietro Antonio is an Italian individual historically known under the full name Pietro Antonio di Vincenzo Stiattesi.
  • D. Francesco
    Francesco is a masculine given name of Italian origin, derived from the Latin Franciscus and commonly associated with figures such as Saint Francis of Assisi.
  • E. Francesco
    Francesco is the given name of Italian actor Franco Nero, renowned for his iconic role in the Spaghetti Western film "Django."
  • 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_69e0b4a81bec8190b69adfdc1336a015 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67992cfb88190ae49a1723e6667a1 completed April 20, 2026, 7:08 p.m.
Created at: April 16, 2026, 11:29 a.m.