Triple
T688295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Zealand Daylight Time |
E13332
|
entity |
| Predicate | observedDuringMonthsApprox |
P14304
|
FINISHED |
| Object | late September to early April |
—
|
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: late September to early April | Statement: [New Zealand Daylight Time, observedDuringMonthsApprox, late September to early April]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: observedDuringMonthsApprox Context triple: [New Zealand Daylight Time, observedDuringMonthsApprox, late September to early April]
-
A.
typicalMonthOfOccurrence
Indicates the month in which something most commonly or typically occurs.
-
B.
appliesDuringMonths
chosen
Indicates that something is valid, active, or in effect only during specific months of the year.
-
C.
hasAverageMonthLength
Indicates that an entity is associated with a specified average length of a month, typically expressed in days.
-
D.
hasMonthCount
Indicates a relationship where an entity is associated with a specific number of months.
-
E.
monthObserved
Indicates the month during which an event, observation, or measurement took place.
- 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0f55f7481909e052a25bd12d455 |
completed | March 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69a49d2048d48190ab99ab59accb6909 |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.