Triple
T6579988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Guinea Coastal Undercurrent |
E157266
|
entity |
| Predicate | variabilityTimescale |
P9981
|
FINISHED |
| Object | seasonal |
—
|
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 | Statement: [New Guinea Coastal Undercurrent, variabilityTimescale, seasonal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: variabilityTimescale Context triple: [New Guinea Coastal Undercurrent, variabilityTimescale, seasonal]
-
A.
timescale
chosen
Indicates the temporal scale or duration over which a process, relationship, or effect occurs or is evaluated.
-
B.
timeScaleOfChange
Indicates the characteristic rate or temporal scale over which a change, process, or transition occurs.
-
C.
timeScaleType
Indicates the type or category of temporal scaling applied to an event, process, or measurement (e.g., real-time, accelerated, aggregated).
-
D.
hasVariability
Indicates that an entity exhibits variation or fluctuation in its state, value, or characteristics over time or across instances.
-
E.
timeScaleRank
Indicates the relative position or priority of a time scale compared to other time scales in a ranked ordering.
- 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_69c6882b3a108190b3a9eb343ae4162c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6c07cdf048190945ca5810fb1de88 |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6acfb462481909cb7aff5af4bca9d |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:54 p.m.