Triple
T15512009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leonida |
E368731
|
entity |
| Predicate | hasCognate |
P2525
|
FINISHED |
| Object | Leonardo |
E1074913
|
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: [Leonida, hasCognate, Leonardo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leonardo Context triple: [Leonida, hasCognate, 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
Leonardo is the katana-wielding, blue-masked leader of the Teenage Mutant Ninja Turtles in the popular comic, TV, and film franchise.
-
C.
Leonardo
"Leonardo" is a historical drama television series that explores the life, genius, and mysteries surrounding Renaissance artist and inventor Leonardo da Vinci.
-
D.
Leonardo
chosen
Leonardo is a masculine given name of Italian origin, historically borne by notable figures such as artists, scientists, and mathematicians.
-
E.
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.
- 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_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e04030c0208190a1931ea130075603 |
completed | April 16, 2026, 1:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3671a4448190b81edae6ff2669a7 |
completed | May 9, 2026, 1:28 p.m. |
Created at: April 10, 2026, 3:56 a.m.