Triple
T2335867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CQF |
E44307
|
entity |
| Predicate | schedulingModel |
P33328
|
FINISHED |
| Object | time-slot based scheduling |
—
|
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: time-slot based scheduling | Statement: [CQF, schedulingModel, time-slot based scheduling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: schedulingModel Context triple: [CQF, schedulingModel, time-slot based scheduling]
-
A.
planningModelFor
chosen
Indicates that one entity serves as a planning model used to guide, simulate, or structure the planning activities related to another entity.
-
B.
concurrentModel
Indicates that two or more processes, activities, or states occur or are valid at the same time, potentially interacting or overlapping in execution.
-
C.
schedule
Indicates that an entity arranges for an event, task, or activity to occur at a specific time or within a defined time frame.
-
D.
executionModel
Indicates how a process, task, or operation is carried out or implemented, specifying the underlying method, strategy, or mechanism of its execution.
-
E.
workModel
Indicates that one entity serves as, or is based on, a particular model used for work, operation, or functional behavior.
- 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_69a889132b488190bbb43ad4780ddd92 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc6f75d888190a2e41edaa532e83f |
completed | March 7, 2026, 6:34 a.m. |
| PD | Predicate disambiguation | batch_69abc594087c819098100a10c5478a4b |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:51 p.m.