Triple
T35333176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyzel in E Flat |
E1020382
|
entity |
| Predicate | performerOccupationOfAddressee |
P24742
|
FINISHED |
| Object | graphic 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: graphic artist | Statement: [Lyzel in E Flat, performerOccupationOfAddressee, graphic artist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: performerOccupationOfAddressee Context triple: [Lyzel in E Flat, performerOccupationOfAddressee, graphic artist]
-
A.
starredPerformerOccupation
Indicates the occupation or professional role of a performer who starred in a work or production.
-
B.
artistOccupation
chosen
Indicates the professional role or job that an artist holds or performs.
-
C.
performerType
Indicates the role or category of performer responsible for carrying out an action or participating in an event.
-
D.
performerDescribedAs
Indicates that a performer is characterized or referred to using a particular description, label, or role.
-
E.
actorNotableOccupation
Indicates that a person (typically an actor) is associated with a particular occupation or professional role for which they are especially well known.
- 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_69f76deacf4481908e7735a5a7715b0a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fefa064ab48190925759950d0d94d9 |
completed | May 9, 2026, 9:10 a.m. |
| PD | Predicate disambiguation | batch_69fef96ae5d08190b027435753c44821 |
completed | May 9, 2026, 9:07 a.m. |
Created at: May 3, 2026, 4:03 p.m.