Triple
T28406548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | INT 10h video services |
E719543
|
entity |
| Predicate | interruptNumber |
P180419
|
FINISHED |
| Object | 0x10 |
—
|
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: 0x10 | Statement: [INT 10h video services, interruptNumber, 0x10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interruptNumber Context triple: [INT 10h video services, interruptNumber, 0x10]
-
A.
numberOfHardwareInterrupts
Indicates the count of hardware interrupt events that have occurred for a given entity or system.
-
B.
junctionNumber
Indicates the identifying number assigned to a specific junction or intersection within a network or system.
-
C.
terminalNumber
Indicates the specific terminal identifier associated with an entity, such as a device, port, or connection point, within a larger system or network.
-
D.
hasInterruptController
Indicates that an entity is associated with or includes an interrupt controller responsible for managing hardware or software interrupts.
-
E.
trapNumber
Indicates that an entity is identified as, or associated with, a specific trap number within a system or context.
- 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_69eff6f0f37c8190b37bc6fab08a9449 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f74062b9388190b30546cf700a825c |
completed | May 3, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69f73c802b848190b61a416b7488bd96 |
completed | May 3, 2026, 12:16 p.m. |
| PDg | Predicate description generation | batch_69f74061c440819080434155c2d60341 |
completed | May 3, 2026, 12:32 p.m. |
Created at: April 28, 2026, 1:23 a.m.