Triple
T8789274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Openbox |
E209119
|
entity |
| Predicate | windowManagementStyle |
P85388
|
FINISHED |
| Object | 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: stacking | Statement: [Openbox, windowManagementStyle, stacking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: windowManagementStyle Context triple: [Openbox, windowManagementStyle, stacking]
-
A.
windowManagement
Indicates the relationship or action of controlling, arranging, or interacting with on-screen windows within a graphical user interface.
-
B.
windowType
Indicates the specific kind or category of window associated with an entity.
-
C.
typicalWindowManagers
Indicates that the subject is associated with or characterized by commonly used or standard window managers.
-
D.
maximizedUnder
Indicates that a quantity, value, or objective reaches its greatest possible level subject to specified conditions or constraints.
-
E.
supportsMultipleWindows
Indicates that the subject can handle or display more than one window or view simultaneously.
- 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_69ca836168108190bb43d3dc235c1f55 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f8b0c108190af53d4bb9b132c5c |
completed | March 31, 2026, 11:58 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1d48f08190b325a77d4c76d223 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cfddef48190aee764ee7b25bae9 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:43 p.m.