Triple
T19435465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TimesTen |
E486214
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | TimesTen Application-Tier Database Cache |
—
|
NE NERFINISHED |
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: TimesTen Application-Tier Database Cache | Statement: [TimesTen, hasComponent, TimesTen Application-Tier Database Cache]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TimesTen Application-Tier Database Cache Context triple: [TimesTen, hasComponent, TimesTen Application-Tier Database Cache]
-
A.
TimesTen
chosen
TimesTen is an in-memory relational database from Oracle designed for extremely low-latency, high-throughput data management and real-time analytics.
-
B.
VoltDB
VoltDB is a high-performance, in-memory, distributed SQL database designed for real-time analytics and transaction processing at massive scale.
-
C.
H-Store
H-Store is a pioneering in-memory, distributed OLTP database system designed for high-throughput transaction processing on modern multicore hardware.
-
D.
Caché
Caché is a tributary stream that feeds into the Bléone River in southeastern France.
-
E.
Actian
Actian is a data management and analytics company known for its hybrid data platforms and database technologies used in enterprise applications.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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.