Triple
T18257703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PROFINET RT |
E437258
|
entity |
| Predicate | latencyClass |
P131053
|
FINISHED |
| Object | real-time |
—
|
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: real-time | Statement: [PROFINET RT, latencyClass, real-time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: latencyClass Context triple: [PROFINET RT, latencyClass, real-time]
-
A.
bandwidthClass
Indicates the classification of a connection or resource based on its available or allocated bandwidth capacity.
-
B.
lengthClass
Indicates a classification relationship where an entity is assigned to a category based on its length.
-
C.
speedClass
Indicates the categorical speed level or range assigned to an entity based on how fast it moves or operates.
-
D.
durabilityClass
Indicates the level or category of resistance an entity has to wear, damage, or degradation over time.
-
E.
depthClass
Indicates the categorical classification of an entity based on its depth or depth-related range.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4fd8879e88190893f8da7c3529496 |
completed | April 19, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69e44fcdee748190bae6fb76e0cb22f3 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a0ba208190a5fe92832a8f7a49 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:34 a.m.