Triple
T17585972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asynchronous Methods for Deep Reinforcement Learning |
E428322
|
entity |
| Predicate | hardwareAssumption |
P33188
|
FINISHED |
| Object | commodity multi-core CPUs |
—
|
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: commodity multi-core CPUs | Statement: [Asynchronous Methods for Deep Reinforcement Learning, hardwareAssumption, commodity multi-core CPUs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hardwareAssumption Context triple: [Asynchronous Methods for Deep Reinforcement Learning, hardwareAssumption, commodity multi-core CPUs]
-
A.
hardwareIncluded
Indicates that certain hardware components are provided or come bundled together with another item or product.
-
B.
hasHardware
Indicates that one entity possesses, includes, or is equipped with specific hardware components or devices.
-
C.
hardwareUsed
chosen
Indicates that a particular piece of hardware is utilized or employed in performing an action, process, or function involving another entity.
-
D.
hasHardwareCompatibilityWith
Indicates that two hardware components or systems can operate together correctly and reliably without conflicts or incompatibilities.
-
E.
checksHardware
Indicates that one entity inspects or verifies the condition, presence, or correctness of another entity’s hardware components.
- 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e463d22f908190ae0f1eeafbe54459 |
completed | April 19, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fff0348190b899a32da537eaca |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:50 a.m.