Triple
T9003991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | macOS SDK |
E215097
|
entity |
| Predicate | supportsDeploymentTarget |
P23634
|
FINISHED |
| Object | multiple macOS versions |
—
|
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: multiple macOS versions | Statement: [macOS SDK, supportsDeploymentTarget, multiple macOS versions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsDeploymentTarget Context triple: [macOS SDK, supportsDeploymentTarget, multiple macOS versions]
-
A.
canBeDeployedUnder
Indicates that one entity is permitted or suitable to be deployed or operated under the conditions, context, or authority defined by another entity.
-
B.
canDeployAs
Indicates that one entity is capable of being deployed or instantiated in the role, form, or environment represented by another entity.
-
C.
hasDeployment
Indicates that an entity is associated with or utilizes a specific deployment instance (e.g., of software, a model, or a system) in an operational context.
-
D.
supportsTargetType
chosen
Indicates that one entity is capable of operating with, handling, or being compatible with a specified target type.
-
E.
supportsAt
Indicates that one entity provides assistance, endorsement, or backing to another entity in a specific context, location, or point in time.
- 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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6959497c8190a748c78504dd2eb6 |
completed | April 1, 2026, 12:39 a.m. |
| PD | Predicate disambiguation | batch_69cc5edd6cb48190b4fc6d6ca0418056 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:05 p.m.