Triple
T11957440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | twm |
E284587
|
entity |
| Predicate | windowManagementModel |
P85388
|
FINISHED |
| Object | manual tiling and stacking |
—
|
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: manual tiling and stacking | Statement: [twm, windowManagementModel, manual tiling and stacking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: windowManagementModel Context triple: [twm, windowManagementModel, manual tiling and stacking]
-
A.
windowManagement
Indicates the relationship or action of controlling, arranging, or interacting with on-screen windows within a graphical user interface.
-
B.
windowManagementStyle
chosen
Indicates how windows are organized, displayed, and controlled within a user interface or system.
-
C.
windowType
Indicates the specific kind or category of window associated with an entity.
-
D.
typicalWindowManagers
Indicates that the subject is associated with or characterized by commonly used or standard window managers.
-
E.
typicalApplicationWindow
Indicates that something is a standard or commonly used application window in a software environment.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903681a00819098c2b5260e2ef834 |
completed | April 10, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3e48e08190b2fee43af4f57323 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.