Triple
T21826431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 100GBASE-KR1 |
E538866
|
entity |
| Predicate | targetDataRatePerLane |
P1376
|
FINISHED |
| Object | 100 Gbit/s |
—
|
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: 100 Gbit/s | Statement: [100GBASE-KR1, targetDataRatePerLane, 100 Gbit/s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetDataRatePerLane Context triple: [100GBASE-KR1, targetDataRatePerLane, 100 Gbit/s]
-
A.
dataRate
chosen
Indicates the rate at which data is transmitted, processed, or transferred between entities over a given time interval.
-
B.
dataRateGeneration
Indicates the rate at which data is produced or generated over time in a given context.
-
C.
laneCount
Indicates the number of parallel lanes associated with a given road or roadway segment.
-
D.
typicalLanes
Indicates the usual or standard number or configuration of lanes associated with a road or similar transportation segment.
-
E.
hasTrackLanes
Indicates that an entity (such as a road or track) includes one or more designated lanes for vehicle or train movement.
- 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_69e0c475038c8190abb9b1a20eb8ff50 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f09132ae888190b8c1a8e75b96b5fd |
completed | April 28, 2026, 10:51 a.m. |
| PD | Predicate disambiguation | batch_69e6be815a108190be81d7c987d0c0d6 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:54 p.m.