Triple
T4326013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | torchvision |
E96634
|
entity |
| Predicate | transformType |
P56260
|
FINISHED |
| Object | Compose |
—
|
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: Compose | Statement: [torchvision, transformType, Compose]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transformType Context triple: [torchvision, transformType, Compose]
-
A.
transformsUnder
Indicates a relationship where one entity changes form, state, or structure when subjected to the influence, conditions, or operation specified by another entity.
-
B.
changeType
Indicates the specific kind or category of modification that has occurred to an entity or relationship.
-
C.
transferFunctionType
Indicates the specific kind or category of transfer function that characterizes how input signals are transformed into output signals in a system.
-
D.
formerType
Indicates that one entity previously had a certain type, role, or classification but no longer does.
-
E.
conversionName
Indicates that one entity is the name or label assigned to a specific conversion event or conversion process associated with another entity.
- 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_69b34542fd908190b11b08faad8decfd |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3513020f481909ff2fec3934f3002 |
completed | March 12, 2026, 11:50 p.m. |
| PD | Predicate disambiguation | batch_69b34f4bec888190987fc2631498b637 |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b3501834448190bedf775a80da4778 |
completed | March 12, 2026, 11:45 p.m. |
Created at: March 12, 2026, 11:13 p.m.