Triple
T1458044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Australia/Lord_Howe |
E31442
|
entity |
| Predicate | dstOffsetChangeMinutes |
P8057
|
FINISHED |
| Object | 30 |
—
|
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: 30 | Statement: [Australia/Lord_Howe, dstOffsetChangeMinutes, 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dstOffsetChangeMinutes Context triple: [Australia/Lord_Howe, dstOffsetChangeMinutes, 30]
-
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.
DSTOffsetChange
chosen
Indicates a change in the time offset applied to a time zone due to the start or end of daylight saving time.
-
C.
offsetDSTDifferenceHours
Indicates the difference in time zone offsets, measured in hours, that results specifically from the application of daylight saving time.
-
D.
historicalOffsetChanges
Indicates that the relationship captures past changes in an offset value between entities, including when and how that offset was modified over time.
-
E.
offsetMagnitudeHours
Indicates the size of a time difference, measured in hours, between two temporal reference points.
- 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_69a49917dfc081909acdbdf5d684f1ef |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c59a462881908e84b27846a6bc04 |
completed | March 1, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69a4c47ec5108190b1772237f2e5d90b |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.