Triple
T29804716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HP Pascal |
E756808
|
entity |
| Predicate | optimizationSupport |
P167891
|
FINISHED |
| Object | code optimization for HP architectures |
—
|
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: code optimization for HP architectures | Statement: [HP Pascal, optimizationSupport, code optimization for HP architectures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: optimizationSupport Context triple: [HP Pascal, optimizationSupport, code optimization for HP architectures]
-
A.
supportsOptimizationAlgorithm
Indicates that one entity is capable of running, integrating, or being compatible with a specified optimization algorithm.
-
B.
optimizationType
Indicates the specific strategy or method used to improve performance or efficiency within a given process or system.
-
C.
optimizationTarget
Indicates that one entity is the goal or objective that another entity is trying to improve, optimize, or make more efficient.
-
D.
optimizationDomain
Indicates the domain, field, or context within which an optimization process or optimization-related activity is applied.
-
E.
optimizationVariant
Indicates that one entity is a specific version or alternative form of another entity created for optimization purposes.
- F. None of above. chosen
Provenance (4 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_69f2245584848190ad4cab1f07752ccb |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f675295a008190a97eebccb578ce81 |
completed | May 2, 2026, 10:05 p.m. |
| PD | Predicate disambiguation | batch_69f66ac1a4fc81909740d2e52fbe6970 |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66c59de9881909ebbb7b0ae7ab495 |
completed | May 2, 2026, 9:27 p.m. |
Created at: April 29, 2026, 5:20 p.m.