Triple
T38309510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regor (cut-down) |
E1033645
|
entity |
| Predicate | hasNumberOfCores |
P11223
|
FINISHED |
| Object | 1 |
—
|
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 | Statement: [Regor (cut-down), hasNumberOfCores, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfCores Context triple: [Regor (cut-down), hasNumberOfCores, 1]
-
A.
hasCPUCore
Indicates that an entity (typically a computing device or processor) possesses or includes a specific CPU core as one of its components.
-
B.
isMultiCore
Indicates that the entity (such as a processor or system) consists of or utilizes multiple processing cores operating together.
-
C.
smallCoreCount
Indicates that an entity has a relatively low number of processing cores compared to typical or expected configurations.
-
D.
supportsProcessorCoreCount
Indicates that one entity is compatible with or able to operate using a specified number of processor cores in another entity.
-
E.
coreCountCPU
chosen
Indicates the number of processing cores that a CPU has.
- 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_69f76e132c408190969b3d35c04b87ae |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff45793d5c81909dc503ad1f714ee2 |
completed | May 9, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69ff41cb0e088190a6e9b03cb20e5fad |
completed | May 9, 2026, 2:16 p.m. |
Created at: May 3, 2026, 4:30 p.m.