Triple
T34479054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donato di Paolo Uccello |
E885127
|
entity |
| Predicate | possibleProfession |
P2374
|
FINISHED |
| Object | artist |
—
|
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: artist | Statement: [Donato di Paolo Uccello, possibleProfession, artist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: possibleProfession Context triple: [Donato di Paolo Uccello, possibleProfession, artist]
-
A.
subjectOccupation
chosen
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
B.
leftProfession
Indicates that an entity has stopped or abandoned a particular profession or occupation they previously held.
-
C.
portraysProfession
Indicates that one entity depicts or represents another entity in a specific profession or occupational role.
-
D.
commonProfessionAmongBearers
Indicates that multiple entities sharing a given attribute (such as a name or title) are frequently associated with the same profession.
-
E.
includesProfession
Indicates that one entity’s set of attributes, roles, or members contains a specific profession as part of it.
- 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_69f349c947fc81909d30b53c194d6ea1 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7764ab1fc81909f9348db87bd7692 |
completed | May 3, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69f76905d9c88190b1ee810bc9ab644f |
completed | May 3, 2026, 3:25 p.m. |
Created at: May 1, 2026, 2:01 a.m.