Triple
T1278479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deep Western Boundary Current |
E27268
|
entity |
| Predicate | timescaleOfVariability |
P9981
|
FINISHED |
| Object | interannual |
—
|
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: interannual | Statement: [Deep Western Boundary Current, timescaleOfVariability, interannual]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timescaleOfVariability Context triple: [Deep Western Boundary Current, timescaleOfVariability, interannual]
-
A.
timescale
chosen
Indicates the temporal scale or duration over which a process, relationship, or effect occurs or is evaluated.
-
B.
hasVariability
Indicates that an entity exhibits variation or fluctuation in its state, value, or characteristics over time or across instances.
-
C.
timeScaleType
Indicates the type or category of temporal scaling applied to an event, process, or measurement (e.g., real-time, accelerated, aggregated).
-
D.
timeContinuousOrDiscrete
Indicates whether the time dimension in a given context is modeled as a continuous flow or as discrete, separate time points.
-
E.
supportsTimescale
Indicates that one entity is capable of operating with, accommodating, or being compatible with a specified timescale or range of temporal resolutions.
- 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_69a496d3710c8190955dee8bc0dacb50 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c31602b8819087a57e8d390cae7a |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4bee0be808190a8ccac6a41851fdd |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:50 p.m.