Triple
T505093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Art Direction |
E10485
|
entity |
| Predicate | includesAspects |
P1393
|
FINISHED |
| Object | set design |
—
|
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: set design | Statement: [Academy Award for Best Art Direction, includesAspects, set design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesAspects Context triple: [Academy Award for Best Art Direction, includesAspects, set design]
-
A.
hasAspectSystem
Indicates that an entity possesses or is associated with a particular aspect system, such as a structured set of characteristics, dimensions, or perspectives.
-
B.
includes
chosen
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
C.
includesApproach
Indicates that one entity incorporates, utilizes, or is characterized by a particular method, strategy, or approach in relation to another entity or context.
-
D.
includesInfraclass
Indicates that one entity is classified as belonging to a specific infraclass within a taxonomic hierarchy.
-
E.
incorporatedAs
Indicates that an organization has been legally formed and registered under a specific corporate structure or name.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f14b2acc8190818e8a53eac69c54 |
completed | Feb. 28, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69a2edfce7a08190a408bc019de60d5d |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.