Triple
T25550479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AVX-512 |
E640424
|
entity |
| Predicate | optimizationConcern |
P158864
|
FINISHED |
| Object | thermal throttling risk |
—
|
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: thermal throttling risk | Statement: [AVX-512, optimizationConcern, thermal throttling risk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: optimizationConcern Context triple: [AVX-512, optimizationConcern, thermal throttling risk]
-
A.
optimizationConcern
chosen
Indicates a relationship where one entity is a factor, issue, or objective that must be considered or addressed during the optimization of another entity or process.
-
B.
optimize
Indicates improving a process, system, or outcome to achieve the best possible performance or efficiency under given constraints.
-
C.
optimizationQuestion
Indicates that one entity poses a query to another about how to improve efficiency, performance, or resource usage in a given context.
-
D.
concernsProvision
Indicates a relationship where something is about, deals with, or relates to the supplying or making available of resources, services, or necessities.
-
E.
concernsFeature
Indicates that something is about, relates to, or involves a particular feature.
- 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_69e75dc101a881909fd33b02174e9768 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f8c583e48190a2a1f65d80a2b589 |
completed | May 2, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69f49377411c8190b2188de444d76795 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 21, 2026, 3:36 p.m.