Triple
T23783253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soya Strait |
E587878
|
entity |
| Predicate | hasSurfaceWaterTemperatureVariation |
P151509
|
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: [Soya Strait, hasSurfaceWaterTemperatureVariation, seasonal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurfaceWaterTemperatureVariation Context triple: [Soya Strait, hasSurfaceWaterTemperatureVariation, seasonal]
-
A.
hasWaterDepthVariation
Indicates that the water body or location exhibits differences in depth across its area or over time.
-
B.
hasTypicalTemperatureVariation
chosen
Indicates that an entity is associated with a characteristic or usual range of temperature change under normal conditions.
-
C.
requiresSeaSurfaceTemperature
Indicates that one entity depends on or needs a specified sea surface temperature condition to occur, function, or be valid.
-
D.
hasTidalRange
Indicates the relationship between a location or body of water and the magnitude of difference between its high and low tide levels.
-
E.
waterTemperatureType
Indicates the classification or category of a water body’s temperature (e.g., cold, warm, hot) associated with an entity or context.
- 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_69e2490f4ad48190b690878eec3596c6 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1c62ea9c0819083544822267d3215 |
completed | April 29, 2026, 8:49 a.m. |
| PD | Predicate disambiguation | batch_69f155f79e34819080f9ddb972b34deb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:16 p.m.