Triple
T2208910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tasman Front |
E50866
|
entity |
| Predicate | hasTemporalVariability |
P13845
|
FINISHED |
| Object | seasonal variability in position |
—
|
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: seasonal variability in position | Statement: [Tasman Front, hasTemporalVariability, seasonal variability in position]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTemporalVariability Context triple: [Tasman Front, hasTemporalVariability, seasonal variability in position]
-
A.
hasVariability
chosen
Indicates that an entity exhibits variation or fluctuation in its state, value, or characteristics over time or across instances.
-
B.
hasDirectionVariability
Indicates that the direction associated with an entity or process is not fixed but varies over time, space, or conditions.
-
C.
temporalAspect
Indicates the time-related characteristics or phase (such as duration, frequency, or temporal status) associated with an event or relationship.
-
D.
hasTemporalLocation
Indicates that something occurs, exists, or is valid during a specific time or time interval.
-
E.
hasVariance
Indicates that there is a measurable degree of variability or dispersion in the values or outcomes associated with the related entities.
- 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_69a88b06709c8190978fb2418470d1b6 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc1baa0948190b07ffc347a4f714e |
completed | March 7, 2026, 6:12 a.m. |
| PD | Predicate disambiguation | batch_69abbda8a6dc8190aa855ce2d17194b1 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.