Triple
T18256085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GHC |
E437224
|
entity |
| Predicate | hasOptimizationLevel |
P56543
|
FINISHED |
| Object | -O0 |
—
|
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: -O0 | Statement: [GHC, hasOptimizationLevel, -O0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOptimizationLevel Context triple: [GHC, hasOptimizationLevel, -O0]
-
A.
optimizationLevel
chosen
Indicates the degree or intensity to which a process, system, or solution has been refined to improve its performance or efficiency.
-
B.
canBeOptimizedFor
Indicates that one entity is capable of being improved or adjusted to perform better with respect to another specified criterion, context, or target.
-
C.
supportsOptimizationAlgorithm
Indicates that one entity is capable of running, integrating, or being compatible with a specified optimization algorithm.
-
D.
hasUsageLevel
Indicates the degree or intensity with which something is used or utilized.
-
E.
hasStandardizationLevel
Indicates the degree or extent to which something conforms to an established standard or set of standardized criteria.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4fd85ee548190a102611fcf709ad4 |
completed | April 19, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69e44fcdee748190bae6fb76e0cb22f3 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:34 a.m.