Triple
T505000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tim Burton |
E10483
|
entity |
| Predicate | hasSignatureVisualStyle |
P14486
|
FINISHED |
| Object | darkly whimsical aesthetics |
—
|
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: darkly whimsical aesthetics | Statement: [Tim Burton, hasSignatureVisualStyle, darkly whimsical aesthetics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignatureVisualStyle Context triple: [Tim Burton, hasSignatureVisualStyle, darkly whimsical aesthetics]
-
A.
signatureStyle
Indicates the characteristic way in which an entity typically signs its name or marks documents, distinguishing its unique signing pattern or format.
-
B.
hasSignFor
Indicates that one entity displays, bears, or provides a sign, symbol, or notice that represents, directs attention to, or gives information about another entity.
-
C.
hasSign
Indicates that an entity possesses, displays, or is associated with a particular sign or symbol.
-
D.
signatureWorkType
Indicates the specific category or type of work that serves as a defining or primary example associated with an entity.
-
E.
signatureImage
Indicates that an entity has an associated image that visually represents its signature.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f149bd1c81908ff58ac504ace2bf |
completed | Feb. 28, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69a2edfce7a08190a408bc019de60d5d |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eebbd70481908b462296671de67b |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.