Triple
T4175952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Infernal Scene |
E86476
|
entity |
| Predicate | creatorSpecialization |
P54223
|
FINISHED |
| Object | hell scenes |
—
|
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: hell scenes | Statement: [Infernal Scene, creatorSpecialization, hell scenes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: creatorSpecialization Context triple: [Infernal Scene, creatorSpecialization, hell scenes]
-
A.
creatorType
Indicates the role or category of a creator in relation to the creation of something (e.g., author, artist, director).
-
B.
creationType
Indicates the manner or process by which something was brought into existence or produced.
-
C.
creatorOccupation
Indicates the professional role or job that the creator of an entity holds or held.
-
D.
portraitSpecialization
Indicates that one entity specializes in creating or working with portraits, distinguishing a focused area of expertise within a broader artistic or professional domain.
-
E.
positionSpecialization
Indicates that one position is a more specialized or focused variant of another, broader position.
- F. None of above. chosen
Provenance (4 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_69aed93de98c8190ad838ce507b77c8a |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af07078cb081909f64326b12522410 |
completed | March 9, 2026, 5:44 p.m. |
| PD | Predicate disambiguation | batch_69af019155448190b19868583272513f |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af07059d288190a1ea79449414fbce |
completed | March 9, 2026, 5:44 p.m. |
Created at: March 9, 2026, 3:45 p.m.