Triple
T7661675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nepal Time |
E173520
|
entity |
| Predicate | offsetMinutes |
P5579
|
FINISHED |
| Object | 45 |
—
|
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: 45 | Statement: [Nepal Time, offsetMinutes, 45]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offsetMinutes Context triple: [Nepal Time, offsetMinutes, 45]
-
A.
offsetSeconds
Indicates a temporal relationship where one event or time point occurs a specified number of seconds before or after another reference time.
-
B.
offsetMagnitudeHours
Indicates the size of a time difference, measured in hours, between two temporal reference points.
-
C.
offsetInSecondsFromUTC
Indicates the time difference, measured in whole seconds, between a given time reference and Coordinated Universal Time (UTC).
-
D.
offsetFromUTCInMinutes
chosen
Indicates the number of minutes by which a given time value differs from Coordinated Universal Time (UTC), positive or negative.
-
E.
offsetDSTDifferenceHours
Indicates the difference in time zone offsets, measured in hours, that results specifically from the application of daylight saving time.
- 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_69c69955517c819085bc715b96d304d2 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7061cbc3c8190a917dd7e71214182 |
completed | March 27, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69c7015dd8fc8190bc5f52a12bd46209 |
completed | March 27, 2026, 10:14 p.m. |
Created at: March 27, 2026, 3:59 p.m.