Triple
T34540363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Python 3.11 |
E886788
|
entity |
| Predicate | averageSpeedupReported |
P55146
|
FINISHED |
| Object | 1.25x |
—
|
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: 1.25x | Statement: [Python 3.11, averageSpeedupReported, 1.25x]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageSpeedupReported Context triple: [Python 3.11, averageSpeedupReported, 1.25x]
-
A.
typicalSpeedup
chosen
Indicates the usual or expected performance improvement (e.g., reduction in time or increase in speed) achieved when applying one method, system, or configuration relative to another.
-
B.
hasAverageSurfaceSpeed
Indicates the typical or mean speed at which something moves across a surface over a given period or distance.
-
C.
speedupType
Indicates the kind or category of performance improvement achieved relative to a baseline.
-
D.
speedAchieved
Indicates that a particular speed has been reached or attained by an entity during an event or action.
-
E.
speedupFormula
Indicates a quantitative relationship expressing how much faster one process or system becomes relative to another, typically as a ratio or factor of performance improvement.
- 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_69f349ce5eb881909e431c670944aa68 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71ff3ae60819089447abe3ff9e784 |
completed | May 3, 2026, 10:14 a.m. |
| PD | Predicate disambiguation | batch_69f71cc8074c81909ae09bea2acf1a09 |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 2:02 a.m.