Triple
T5150638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TAI |
E116183
|
entity |
| Predicate | timeScaleClass |
P62232
|
FINISHED |
| Object | atomic time |
—
|
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: atomic time | Statement: [TAI, timeScaleClass, atomic time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeScaleClass Context triple: [TAI, timeScaleClass, atomic time]
-
A.
timeScaleType
Indicates the type or category of temporal scaling applied to an event, process, or measurement (e.g., real-time, accelerated, aggregated).
-
B.
timeScaleUnit
Indicates the unit of temporal measurement (such as seconds, minutes, or hours) used to express a given time scale.
-
C.
timeScaleStandard
Indicates the standard or convention used to define, measure, or interpret the time scale associated with an event or process.
-
D.
timescale
Indicates the temporal scale or duration over which a process, relationship, or effect occurs or is evaluated.
-
E.
timeSampling
Indicates that one entity specifies how or at what intervals another entity is sampled or measured over time.
- 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_69bd445d94788190b72e2cc563120995 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79c1354c81908176703b4853c1a4 |
completed | March 20, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69bd77b0fbb88190851e2d7ae1bdcc09 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd79bf9b088190a556dc02f10204e4 |
completed | March 20, 2026, 4:45 p.m. |
Created at: March 20, 2026, 1:44 p.m.