Triple
T4260463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fast Ethernet |
E96089
|
entity |
| Predicate | frameSizeMaximum |
P55005
|
FINISHED |
| Object | 1518 bytes (without VLAN tag) |
—
|
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: 1518 bytes (without VLAN tag) | Statement: [Fast Ethernet, frameSizeMaximum, 1518 bytes (without VLAN tag)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frameSizeMaximum Context triple: [Fast Ethernet, frameSizeMaximum, 1518 bytes (without VLAN tag)]
-
A.
frameSize
Indicates the size or dimensions of a frame associated with an entity.
-
B.
minimumFrameSize
Indicates the smallest allowable or supported size of a frame in the given context or system.
-
C.
inputFrameSize
Indicates the size or dimensions of the input frame used or processed in a given context.
-
D.
maximumBitrate
Indicates the highest data transfer rate allowed or supported for a given media stream or connection.
-
E.
maximumChannelWidth
Indicates the greatest allowable or observed width of a channel in the given context.
- 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_69b3454095ac81909c2494f7ff294af1 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34f8103b48190934a810faafa6cb7 |
completed | March 12, 2026, 11:42 p.m. |
| PD | Predicate disambiguation | batch_69b347f73e008190a908a48ef389945a |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e04ef1c81908bb34ae1cbfab1e6 |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:06 p.m.