Triple
T7322788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IEEE 802.1Qcj |
E168791
|
entity |
| Predicate | targetTraffic |
P621
|
FINISHED |
| Object | time-sensitive traffic |
—
|
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: time-sensitive traffic | Statement: [IEEE 802.1Qcj, targetTraffic, time-sensitive traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetTraffic Context triple: [IEEE 802.1Qcj, targetTraffic, time-sensitive traffic]
-
A.
trafficType
chosen
Indicates the category or nature of traffic involved in a given interaction, flow, or connection (e.g., type of network, data, or transport traffic).
-
B.
trafficFocus
Indicates a focus of attention or priority given to a particular traffic element, flow, or direction within a transportation or network context.
-
C.
annualTraffic
Indicates the typical amount or volume of traffic associated with something over the course of a year.
-
D.
originalTrafficType
Indicates the initial category or source classification of traffic before any changes, redirects, or reattributions occur.
-
E.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
- 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_69c68a54cacc81908e3b773441f19566 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0446628819093e96236f1aa4a9b |
completed | March 27, 2026, 9:01 p.m. |
| PD | Predicate disambiguation | batch_69c6e77230048190b2c29ca6b3a65b8e |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3:03 p.m.