Triple
T14434086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michel-Ange – Auteuil |
E357912
|
entity |
| Predicate | isNamedForTheme |
P24365
|
FINISHED |
| Object | Italian Renaissance artist Michelangelo |
—
|
LITERAL 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: Italian Renaissance artist Michelangelo | Statement: [Michel-Ange – Auteuil, isNamedForTheme, Italian Renaissance artist Michelangelo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNamedForTheme Context triple: [Michel-Ange – Auteuil, isNamedForTheme, Italian Renaissance artist Michelangelo]
-
A.
isNamedFor
chosen
Indicates that one entity bears its name in honor of, or derived from, another entity.
-
B.
isNamedForPersonFrom
Indicates that an entity is named after a person who originates from a specified place or region.
-
C.
themedAs
Indicates that something is characterized, styled, or organized according to a particular theme or motif.
-
D.
hasNicknameTheme
Indicates that an entity’s nickname is based on or associated with a particular theme or motif.
-
E.
usesThemeFrom
Indicates that one work incorporates, references, or is based on the thematic material of another work.
- F. None of above.
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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91471a648190adb7b283a6a85c3e |
completed | April 14, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69de5c3a02fc819097373f97a260cdeb |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:18 a.m.