Triple
T36488911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2.5D sketch |
E899003
|
entity |
| Predicate | levelOfProcessing |
P186512
|
FINISHED |
| Object | mid-level vision |
—
|
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: mid-level vision | Statement: [2.5D sketch, levelOfProcessing, mid-level vision]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: levelOfProcessing Context triple: [2.5D sketch, levelOfProcessing, mid-level vision]
-
A.
curationLevel
Indicates the degree or extent to which something has been deliberately selected, organized, or refined by a curator or curatorial process.
-
B.
automationLevel
Indicates the degree to which a process, task, or system is performed automatically rather than manually.
-
C.
processingUse
Indicates that one entity uses or applies another entity as part of a processing or transformation activity.
-
D.
dataProcessingStyle
Indicates the manner, method, or approach by which data is processed or handled in a given context.
-
E.
classificationLevel
Indicates the degree or tier within an ordered system or hierarchy to which something is assigned for categorization or control purposes.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f9fe1a1ca4819084c196f0041f0be2 |
completed | May 5, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
| PDg | Predicate description generation | batch_69f9fd66eed48190bdc26a8def328c2d |
completed | May 5, 2026, 2:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.