Triple

T2852002
Position Surface form Disambiguated ID Type / Status
Subject Leonhard E63113 entity
Predicate hasVariant P455 FINISHED
Object Leonardo E22299 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: [Leonhard, hasVariant, Leonardo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leonardo
Context triple: [Leonhard, hasVariant, Leonardo]
  • A. Leonardo
    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 chosen
    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_69ab4c407c408190857d25e027155ce9 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf5ca2648190bd32c6ec4b0dd3b6 completed March 7, 2026, 8:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8e4e0b881908de5c4927609725e completed March 10, 2026, 9:48 a.m.
Created at: March 6, 2026, 10:02 p.m.