Triple
T1649854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Intel 8088 |
E35665
|
entity |
| Predicate | instructionQueueLength |
P30866
|
FINISHED |
| Object | 4 bytes |
—
|
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: 4 bytes | Statement: [Intel 8088, instructionQueueLength, 4 bytes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: instructionQueueLength Context triple: [Intel 8088, instructionQueueLength, 4 bytes]
-
A.
queueType
Indicates the classification or category of a queue that specifies how items in it are organized, prioritized, or processed.
-
B.
isBusiestInSystem
Indicates that an entity has the highest level of activity or load compared to all other entities within the same system.
-
C.
numberOfQueries
Indicates the total count of queries associated with or performed in a given context or entity.
-
D.
receiveFiberCount
Indicates that an entity obtains or is assigned a specific number of fiber units from another source or process.
-
E.
instructionSetSize
Indicates the size or number of instructions defined in an instruction set.
- 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_69a8860568888190a32cd9f70acbba42 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaa0fbe984819084f8daee81ca9b67 |
completed | March 6, 2026, 9:40 a.m. |
| PD | Predicate disambiguation | batch_69a907ce4dd881909168a1e99505d4ec |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a949509d508190a3a35554996823de |
completed | March 5, 2026, 9:13 a.m. |
Created at: March 4, 2026, 7:29 p.m.