Triple
T6961682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adobe Bridge |
E161383
|
entity |
| Predicate | supportsFileType |
P24486
|
FINISHED |
| Object | image files |
—
|
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: image files | Statement: [Adobe Bridge, supportsFileType, image files]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsFileType Context triple: [Adobe Bridge, supportsFileType, image files]
-
A.
supportsType
chosen
Indicates that one entity is capable of handling, accepting, or being compatible with a specified type.
-
B.
supportsProjectType
Indicates that one entity is capable of handling, accommodating, or being compatible with a specified type of project.
-
C.
supportsModelType
Indicates that an entity is compatible with, or can operate using, a specified model type.
-
D.
supportsTargetType
Indicates that one entity is capable of operating with, handling, or being compatible with a specified target type.
-
E.
supportsProgramType
Indicates that one entity is capable of handling, offering, or being compatible with a specified type of program.
- 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_69c68853cff881908439d488924a8283 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6daf07e3481909aa79b8e0f1b1be7 |
completed | March 27, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c0b0a08190b262dfc94992994d |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:30 p.m.