Triple
T30300056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NSOperationQueue |
E770629
|
entity |
| Predicate | mainQueueUsedFor |
P161803
|
FINISHED |
| Object | executing operations on main thread |
—
|
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: executing operations on main thread | Statement: [NSOperationQueue, mainQueueUsedFor, executing operations on main thread]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainQueueUsedFor Context triple: [NSOperationQueue, mainQueueUsedFor, executing operations on main thread]
-
A.
usesQueue
Indicates that one entity employs or relies on a queue mechanism to manage or process items, tasks, or messages.
-
B.
hasQueue
Indicates that an entity maintains or is associated with a queue, typically representing an ordered list of items or tasks awaiting processing.
-
C.
usesVirtualQueueSystem
Indicates that an entity manages access or service order through a virtual queuing mechanism rather than a traditional physical line.
-
D.
mainUseCase
chosen
Indicates the primary purpose or most common scenario in which something is intended to be used.
-
E.
queueType
Indicates the classification or category of a queue that specifies how items in it are organized, prioritized, or processed.
- 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_69f224881b948190b8c4921b250a44a3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6813976048190be49bb86744b2fb2 |
completed | May 2, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69f6760216108190bbb708d53a6c2c25 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:48 p.m.