Triple
T3131310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple silicon Mac Pro models |
E65418
|
entity |
| Predicate | advantageOverPredecessor |
P7339
|
FINISHED |
| Object | improved performance per watt |
—
|
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: improved performance per watt | Statement: [Apple silicon Mac Pro models, advantageOverPredecessor, improved performance per watt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: advantageOverPredecessor Context triple: [Apple silicon Mac Pro models, advantageOverPredecessor, improved performance per watt]
-
A.
improvesOn
Indicates that one entity enhances, refines, or performs better than another entity, typically by addressing its limitations or increasing its effectiveness.
-
B.
predecessor
Indicates that one entity comes before another in an ordered sequence or succession.
-
C.
typicalEfficiencyComparedToPredecessor
Indicates how the usual or average efficiency of something compares to that of its predecessor.
-
D.
successorUse
Indicates that one entity is used or applied as the subsequent or follow-up use of another entity in a sequence or lifecycle.
-
E.
notableAdvantage
chosen
Indicates that one entity possesses a significant benefit, edge, or favorable quality over another entity or in a given context.
- 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_69ad8581c25c8190b0d85ba9b9baa531 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada54b0e688190b691771f17f4c721 |
completed | March 8, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_69ad9df62e548190b053e1478deed467 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:04 p.m.