Triple
T12324297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazon EBS |
E293788
|
entity |
| Predicate | durabilityModel |
P104473
|
FINISHED |
| Object | replicated within an Availability Zone |
—
|
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: replicated within an Availability Zone | Statement: [Amazon EBS, durabilityModel, replicated within an Availability Zone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: durabilityModel Context triple: [Amazon EBS, durabilityModel, replicated within an Availability Zone]
-
A.
durabilityClass
Indicates the level or category of resistance an entity has to wear, damage, or degradation over time.
-
B.
durabilityLossRate
Indicates the rate at which an entity’s durability decreases over time or use.
-
C.
durabilityLossCondition
Indicates the specific circumstances or events under which an object's durability decreases.
-
D.
mechanicalDurability
Indicates the ability of something to withstand mechanical forces, stresses, or wear without failing or degrading.
-
E.
consistencyModel
Indicates that one entity adheres to, implements, or is governed by a particular consistency model in its behavior or operations.
- 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_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. |
| PDg | Predicate description generation | batch_69d93f607a88819089e89fd263ae9937 |
completed | April 10, 2026, 6:20 p.m. |
Created at: April 8, 2026, 9:53 p.m.