Triple
T1718481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KVM |
E37340
|
entity |
| Predicate | supportsTechnology |
P5090
|
FINISHED |
| Object | Intel VT-x |
E163095
|
NE 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: Intel VT-x | Statement: [KVM, supportsTechnology, Intel VT-x]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Intel VT-x Context triple: [KVM, supportsTechnology, Intel VT-x]
-
A.
Intel VT-x
chosen
Intel VT-x is Intel's hardware-assisted virtualization technology that enables more efficient and secure running of multiple operating systems on x86 processors.
-
B.
Intel VT-d
Intel VT-d is Intel’s hardware-assisted I/O virtualization technology that enables secure and efficient direct device assignment to virtual machines.
-
C.
VMX
VMX is a vector processing extension to the PowerPC architecture designed to accelerate multimedia, signal processing, and other parallelizable computations.
-
D.
Intel 64
Intel 64 is Intel’s 64-bit architecture extension that enables x86 processors to handle 64-bit computing, including larger memory addressing and enhanced performance for modern applications.
-
E.
Intel AVX
Intel AVX is an x86 processor instruction set extension from Intel that accelerates floating-point and vector-intensive workloads, commonly used in high-performance computing, multimedia, and scientific applications.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a8861912dc8190931af43b4b9158a7 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa6337d8408190bdba8b50652d50ae |
completed | March 6, 2026, 5:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8ae6940c81909c1ebdfb0cdef5fc |
completed | March 8, 2026, 2:42 p.m. |
Created at: March 4, 2026, 7:30 p.m.