Triple
T10067890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | POWER2 |
E213144
|
entity |
| Predicate | supportsOutOfOrderExecution |
P74580
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [POWER2, supportsOutOfOrderExecution, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsOutOfOrderExecution Context triple: [POWER2, supportsOutOfOrderExecution, false]
-
A.
outOfOrderExecution
chosen
Indicates that actions or operations are carried out in a sequence different from their original or logically expected order.
-
B.
supportsBatchProcessing
Indicates that the subject can handle multiple items or tasks in a single grouped operation rather than processing them individually.
-
C.
orderingGuarantee
Indicates that there is a constraint on the relative order in which related events, operations, or messages must occur or be observed.
-
D.
supportsConcurrentModelExecution
Indicates that one entity enables or allows multiple models to be executed at the same time without mutual interference.
-
E.
supportsDynamicBatching
Indicates that an entity is capable of handling or processing variable-sized batches of items or requests at runtime, rather than requiring a fixed batch size.
- 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_69ca83977128819084084eb7d1d8c52a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcff798bc8190a84af7bedea66f0a |
completed | April 2, 2026, 2:09 a.m. |
| PD | Predicate disambiguation | batch_69cd4b92573481909389bc6148ae7ea8 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 8:58 p.m.