Triple
T12324370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazon EFS |
E293789
|
entity |
| Predicate | supportsPerformanceMode |
P99857
|
FINISHED |
| Object | General Purpose |
—
|
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: General Purpose | Statement: [Amazon EFS, supportsPerformanceMode, General Purpose]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsPerformanceMode Context triple: [Amazon EFS, supportsPerformanceMode, General Purpose]
-
A.
supportedMode
chosen
Indicates that a system, device, or component is capable of operating in or handling a particular mode.
-
B.
typicalPerformanceMode
Indicates the usual or most common way in which an entity performs an action or operates.
-
C.
performanceFeature
Indicates that an entity possesses a characteristic, capability, or attribute specifically related to its performance or operational effectiveness.
-
D.
supportsAutoLowLatencyMode
Indicates that the subject is capable of automatically enabling and managing a low-latency mode for its operations or interactions.
-
E.
performanceModel
Indicates a relationship where one entity serves as a performance model that represents, predicts, or characterizes the performance behavior of another entity.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec5be788190b82d2edc6a0f1095 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.