Triple
T22313355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 400GBASE-CR4 |
E551579
|
entity |
| Predicate | parallelLanes |
P18336
|
FINISHED |
| Object | 4 parallel lanes |
—
|
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: 4 parallel lanes | Statement: [400GBASE-CR4, parallelLanes, 4 parallel lanes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parallelLanes Context triple: [400GBASE-CR4, parallelLanes, 4 parallel lanes]
-
A.
originalLanes
Indicates that one entity represents the initial or previously existing set or configuration of lanes in relation to another entity.
-
B.
hasLanes
Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
-
C.
hasDedicatedLanes
Indicates that specific lanes within a route or roadway are reserved exclusively for a particular type of traffic or use.
-
D.
usesPhysicalLanes
Indicates that an entity operates or organizes movement through distinct, physically separated lanes or pathways.
-
E.
laneCount
chosen
Indicates the number of parallel lanes associated with a given road or roadway segment.
- 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_69e11e4776588190abb21e5cea79973f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15750f76c81909d6f788928f503f1 |
completed | April 29, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69e73004d9e88190bb862319a5aea06b |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:42 p.m.