Triple
T19435495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oracle Database In-Memory |
E486215
|
entity |
| Predicate | supportsFeature |
P203
|
FINISHED |
| Object | In-Memory FastStart |
—
|
NE NERFINISHED |
How this triple was built (3 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: In-Memory FastStart | Statement: [Oracle Database In-Memory, supportsFeature, In-Memory FastStart]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: In-Memory FastStart Context triple: [Oracle Database In-Memory, supportsFeature, In-Memory FastStart]
-
A.
Oracle Database In-Memory
Oracle Database In-Memory is an optional feature of the Oracle Database that accelerates analytic and mixed workloads by storing data in a dual-format architecture, including a highly optimized in-memory columnar format.
-
B.
xVelocity in-memory analytics engine
xVelocity in-memory analytics engine is a columnar, in-memory data processing engine developed by Microsoft to enable fast, compressed, and scalable analytical querying for business intelligence tools.
-
C.
SPICE in-memory engine
SPICE in-memory engine is Amazon QuickSight’s high-performance, columnar, in-memory data store designed to enable fast, scalable, and interactive analytics on large datasets.
-
D.
Fast File System
Fast File System is a high-performance disk file system used by AmigaOS to improve speed and efficiency over its earlier standard file system.
-
E.
H-Store
H-Store is a pioneering in-memory, distributed OLTP database system designed for high-throughput transaction processing on modern multicore hardware.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: In-Memory FastStart Target entity description: In-Memory FastStart is an Oracle Database In-Memory feature that accelerates database startup by persisting in-memory columnar data to disk for rapid repopulation after restarts.
-
A.
Oracle Database In-Memory
chosen
Oracle Database In-Memory is an optional feature of the Oracle Database that accelerates analytic and mixed workloads by storing data in a dual-format architecture, including a highly optimized in-memory columnar format.
-
B.
xVelocity in-memory analytics engine
xVelocity in-memory analytics engine is a columnar, in-memory data processing engine developed by Microsoft to enable fast, compressed, and scalable analytical querying for business intelligence tools.
-
C.
SPICE in-memory engine
SPICE in-memory engine is Amazon QuickSight’s high-performance, columnar, in-memory data store designed to enable fast, scalable, and interactive analytics on large datasets.
-
D.
Fast File System
Fast File System is a high-performance disk file system used by AmigaOS to improve speed and efficiency over its earlier standard file system.
-
E.
H-Store
H-Store is a pioneering in-memory, distributed OLTP database system designed for high-throughput transaction processing on modern multicore hardware.
- F. None of above.
Provenance (2 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6336001488190a05f372779711ed2 |
completed | April 20, 2026, 2:08 p.m. |
Created at: April 10, 2026, 1:37 p.m.