Triple
T10067907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | POWER2 |
E213144
|
entity |
| Predicate | supportsBranchPrediction |
P91930
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [POWER2, supportsBranchPrediction, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsBranchPrediction Context triple: [POWER2, supportsBranchPrediction, true]
-
A.
supportsAVX
Indicates that one entity provides or is compatible with AVX (Advanced Vector Extensions) functionality for another entity or operation.
-
B.
supportsAVX2
Indicates that one entity provides or has compatibility with AVX2 (Advanced Vector Extensions 2) instruction set capabilities for another.
-
C.
supportsBruteForceSpeedOptimization
Indicates that one entity enables or provides mechanisms for another entity to perform brute-force operations more quickly or efficiently.
-
D.
supportsOptimizationAlgorithm
Indicates that one entity is capable of running, integrating, or being compatible with a specified optimization algorithm.
-
E.
supportsInferenceOf
Indicates that one entity provides a logical basis or justification for concluding or deriving another entity.
- 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_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. |
| PDg | Predicate description generation | batch_69cd4f8d9b888190b8067bd916dae773 |
completed | April 1, 2026, 5:02 p.m. |
Created at: March 30, 2026, 8:58 p.m.