Triple
T17561710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazon Aurora |
E427707
|
entity |
| Predicate | supportsDatabaseModel |
P19966
|
FINISHED |
| Object | relational model |
—
|
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: relational model | Statement: [Amazon Aurora, supportsDatabaseModel, relational model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsDatabaseModel Context triple: [Amazon Aurora, supportsDatabaseModel, relational model]
-
A.
supportsDatabaseConnectivity
Indicates that an entity provides the capability to establish and maintain connections to a database system.
-
B.
supportsDatabaseAbstraction
Indicates that one entity provides or enables a database abstraction layer for another, allowing interaction with databases independently of specific database implementations.
-
C.
supportsModelType
chosen
Indicates that an entity is compatible with, or can operate using, a specified model type.
-
D.
supportsDatabaseAbstractionLayer
Indicates that one entity provides or is compatible with a database abstraction layer used by another entity for interacting with databases independently of specific database implementations.
-
E.
hasDatabase
Indicates that an entity possesses, uses, or is associated with a specific database.
- 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e456274c888190ac80402e391674dd |
completed | April 19, 2026, 4:12 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fd7d048190b54ee4c6155612a5 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:50 a.m.