Triple
T2108326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Network Time Protocol |
E42445
|
entity |
| Predicate | firstSpecified |
P35884
|
FINISHED |
| Object | 1985 |
—
|
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: 1985 | Statement: [Network Time Protocol, firstSpecified, 1985]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstSpecified Context triple: [Network Time Protocol, firstSpecified, 1985]
-
A.
firstOf
Indicates that one entity is the earliest or initial member in an ordered sequence or collection relative to the others.
-
B.
recognizedFirstBy
Indicates that one entity was the earliest or initial recognizer, identifier, or acknowledger of another entity.
-
C.
firstPresentedFor
Indicates that one entity was initially introduced, submitted, or shown to another entity at a particular time or context.
-
D.
firstWord
Indicates that one entity is the first word in the sequence or text associated with another entity.
-
E.
firstOccupied
Indicates that an entity was the initial or earliest occupant of a particular place, position, or resource.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69abb9ce3ff08190a9501f8bb821c01c |
completed | March 7, 2026, 5:38 a.m. |
Created at: March 4, 2026, 7:43 p.m.