Triple
T14420908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GameStream |
E357579
|
entity |
| Predicate | latencyOptimization |
P45126
|
FINISHED |
| Object | designed for minimal input lag |
—
|
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: designed for minimal input lag | Statement: [GameStream, latencyOptimization, designed for minimal input lag]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: latencyOptimization Context triple: [GameStream, latencyOptimization, designed for minimal input lag]
-
A.
communicationLatency
chosen
Indicates the time delay between when a communication is sent by one entity and when it is received or processed by another.
-
B.
optimize
Indicates improving a process, system, or outcome to achieve the best possible performance or efficiency under given constraints.
-
C.
optimizesTrafficFor
Indicates a relationship where one entity adjusts or manages traffic conditions to improve efficiency, flow, or performance for another entity or context.
-
D.
optimizationLevel
Indicates the degree or intensity to which a process, system, or solution has been refined to improve its performance or efficiency.
-
E.
powerOptimizationFor
Indicates a relationship where one entity is used to improve, manage, or optimize the power consumption or power efficiency of another entity.
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de910eb354819089d5d5a46919eb49 |
completed | April 14, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69de5c30467881908e770e3940295641 |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:18 a.m.