Triple
T8284348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RT-Thread |
E193753
|
entity |
| Predicate | supportsMemoryModel |
P12985
|
FINISHED |
| Object | static memory allocation |
—
|
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: static memory allocation | Statement: [RT-Thread, supportsMemoryModel, static memory allocation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsMemoryModel Context triple: [RT-Thread, supportsMemoryModel, static memory allocation]
-
A.
memoryModel
chosen
Indicates a relationship where an entity serves as or uses a specific model or framework for representing, organizing, or managing memory.
-
B.
supportsMemoryProtection
Indicates that one entity provides mechanisms to prevent unauthorized access or interference with another entity’s memory space.
-
C.
supportsECCMemory
Indicates that one entity provides compatibility with or the capability to use ECC (Error-Correcting Code) memory in relation to another entity.
-
D.
supportsMultithreading
Indicates that the subject is capable of executing multiple threads concurrently within the same process.
-
E.
supportsByteAddressing
Indicates that one entity provides the capability for direct access to individual bytes within its addressable memory or data space for another entity.
- 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_69ca82e217a48190880695635c44b2ed |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7ad0535081908bb234cfc0e32b32 |
completed | March 31, 2026, 7:42 a.m. |
| PD | Predicate disambiguation | batch_69cb70ad9fc081908741f8c4a4141edf |
completed | March 31, 2026, 6:58 a.m. |
Created at: March 30, 2026, 5:52 p.m.