Triple
T27612365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Time Protocol |
E700358
|
entity |
| Predicate | supportsSubSecondPrecision |
P199835
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [Time Protocol, supportsSubSecondPrecision, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsSubSecondPrecision Context triple: [Time Protocol, supportsSubSecondPrecision, false]
-
A.
supportsTimePrimitives
Indicates that one entity provides or is compatible with basic time-related constructs or operations used by another entity.
-
B.
supportsLeapSecondInfo
Indicates that an entity is capable of providing or handling information related to leap seconds.
-
C.
hasDatePrecision
Indicates that a date value is associated with a specific level of granularity or exactness (such as year, month, day, or time).
-
D.
supportsTimestamps
Indicates that the subject is capable of handling, storing, or recognizing timestamp information associated with relevant data or events.
-
E.
supportsTimescale
Indicates that one entity is capable of operating with, accommodating, or being compatible with a specified timescale or range of temporal resolutions.
- 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_69ef6a4f1d9c8190b0705acda054368d |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69ff5b233e9c8190adc06cca0758986b |
completed | May 9, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69ff5a5682108190a006b23c4fcdcc7c |
completed | May 9, 2026, 4:01 p.m. |
| PDg | Predicate description generation | batch_69ff5b224b8c8190bd0955876098ecc8 |
completed | May 9, 2026, 4:04 p.m. |
Created at: April 27, 2026, 2:11 p.m.