Triple

T2426580
Position Surface form Disambiguated ID Type / Status
Subject Leonard E53541 entity
Predicate hasCognate P2525 FINISHED
Object Leonardo E54658 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: Leonardo | Statement: [Leonard, hasCognate, Leonardo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leonardo
Context triple: [Leonard, hasCognate, Leonardo]
  • A. Leonardo chosen
    Leonardo is the first name of Leonardo DiCaprio, the acclaimed American actor and environmental activist known for films such as Titanic and Inception.
  • B. Leonardo da Vinci
    Leonardo da Vinci was a Renaissance polymath renowned as a master painter, inventor, scientist, and engineer whose works and ideas profoundly influenced art and science.
  • C. Lorenzo
    Lorenzo is a masculine given name of Italian origin, historically borne by notable figures such as the Renaissance humanist Lorenzo Valla.
  • D. Raphael
    Raphael is an archangel in Judeo-Christian tradition, often associated with healing, guidance, and protection.
  • E. Raphael
    Raphael was a master Italian High Renaissance painter and architect renowned for his harmonious compositions and influential work in both painting and church design.
  • 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_69ab495c44d48190b7235b23719bc3f6 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc99b95548190b77d36de9adfe3bb completed March 7, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef0a5fc208190a2479de4b1344759 completed March 9, 2026, 4:09 p.m.
Created at: March 6, 2026, 9:42 p.m.