Triple
T32515170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azure Storage |
E831041
|
entity |
| Predicate | offersRedundancyModel |
P194527
|
FINISHED |
| Object | Locally Redundant Storage |
—
|
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: Locally Redundant Storage | Statement: [Azure Storage, offersRedundancyModel, Locally Redundant Storage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersRedundancyModel Context triple: [Azure Storage, offersRedundancyModel, Locally Redundant Storage]
-
A.
availabilityModel
Indicates how and under what conditions an entity is available for use, access, or interaction.
-
B.
offeredOnModelType
Indicates that something is made available or provided specifically for a particular model type.
-
C.
compatibilityModel
Indicates that one entity is defined or evaluated according to a specific compatibility framework, standard, or model in relation to another entity.
-
D.
possibleModel
Indicates that one entity can serve as a potential or candidate model or template for another entity.
-
E.
offersHybridVariantIn
Indicates that an entity provides a hybrid (e.g., partially electric or mixed-mode) version of a product or service within a specified context, such as a market, region, or model line.
- 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_69f3492318348190ba37fb6b5f1d67f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd783fed9c81909e792702636c4f1f |
completed | May 8, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69fd7788e63c81909de22fdafcfe41c0 |
completed | May 8, 2026, 5:41 a.m. |
| PDg | Predicate description generation | batch_69fd783e9e5c819087dec7fefa03700d |
completed | May 8, 2026, 5:44 a.m. |
Created at: May 1, 2026, 1 a.m.