Triple
T2108335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Network Time Protocol |
E42445
|
entity |
| Predicate | typicalAccuracy |
P13474
|
FINISHED |
| Object | within a few milliseconds over the public Internet |
—
|
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: within a few milliseconds over the public Internet | Statement: [Network Time Protocol, typicalAccuracy, within a few milliseconds over the public Internet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAccuracy Context triple: [Network Time Protocol, typicalAccuracy, within a few milliseconds over the public Internet]
-
A.
accuracyCivilianTypical
Indicates the degree to which something typically achieves accurate results or effects when applied to civilians.
-
B.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
C.
typicalAssumption
Indicates that something is taken as a standard or default assumption that generally holds in typical or normal circumstances.
-
D.
typicalRange
chosen
Indicates the usual or expected range of values, conditions, or states within which something normally occurs or applies.
-
E.
typicalMatchType
Indicates the usual or most common type of match or pairing that characterizes how two entities are related or aligned.
- 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_69a8871040f08190aac2e2d0ab6b47ad |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbae03f308190841f5a419bb821f6 |
completed | March 7, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69abb7b7b6288190afa11b4d93bd5666 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.