Triple
T20139256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Link Aggregation Control Protocol |
E491114
|
entity |
| Predicate | fastPeriodicInterval |
P63472
|
FINISHED |
| Object | 1 second |
—
|
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: 1 second | Statement: [Link Aggregation Control Protocol, fastPeriodicInterval, 1 second]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fastPeriodicInterval Context triple: [Link Aggregation Control Protocol, fastPeriodicInterval, 1 second]
-
A.
hasInterval
chosen
Indicates that something is associated with a specific span or range between two points in time, space, or value.
-
B.
usesIntervalRatio
Indicates that one entity employs or is based on a specific proportional relationship between two intervals.
-
C.
originalTimeInterval
Indicates the initial or primary time span during which an event, state, or relationship is considered to occur, before any adjustments or derived intervals.
-
D.
laterFrequency
Indicates that one event, state, or action occurs with a lower frequency than another in a temporal sequence.
-
E.
rotationPeriod_hours
Indicates the length of time, measured in hours, that an object takes to complete one full rotation on its axis.
- 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667698a188190869c18b925dba2ed |
completed | April 20, 2026, 5:50 p.m. |
| PD | Predicate disambiguation | batch_69e54cfb0d0081908e789b9b57e96668 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:32 p.m.