Triple
T35627604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Controller Area Network |
E1029497
|
entity |
| Predicate | frameTypes |
P76579
|
FINISHED |
| Object | data frame |
—
|
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: data frame | Statement: [Controller Area Network, frameTypes, data frame]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frameTypes Context triple: [Controller Area Network, frameTypes, data frame]
-
A.
frameType
Indicates the specific structural or categorical kind of frame associated with an entity or relation.
-
B.
framesAs
Indicates how one entity presents, characterizes, or interprets another entity or situation in a particular light or context.
-
C.
frame
Indicates placing or presenting something within a particular context, structure, or perspective that shapes how it is interpreted.
-
D.
frameShape
Indicates that one entity has the specified geometric or structural shape of a frame in relation to another entity.
-
E.
hasFrameType
chosen
Indicates that an entity possesses or is associated with a specific type or category of frame.
- 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_69f76e07bb0c8190968ea2d836fc42c9 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79f15e6ac8190916822e28724534a |
completed | May 3, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69f79e4bdbcc8190be7a0d2cf8a77b64 |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:05 p.m.