Triple
T749697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tasman Sea |
E15418
|
entity |
| Predicate | typicalWaveConditions |
P13023
|
FINISHED |
| Object | frequent large swells |
—
|
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: frequent large swells | Statement: [Tasman Sea, typicalWaveConditions, frequent large swells]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWaveConditions Context triple: [Tasman Sea, typicalWaveConditions, frequent large swells]
-
A.
hasSeaCondition
chosen
Indicates that an entity is associated with or characterized by a particular state or condition of the sea.
-
B.
typicalStormType
Indicates the kind of storm that is most commonly or characteristically associated with a given context or location.
-
C.
hasTidalRange
Indicates the relationship between a location or body of water and the magnitude of difference between its high and low tide levels.
-
D.
prevailingSurfaceWinds
Indicates the typical or most frequently occurring wind direction and speed that dominate at a given location over a specified period.
-
E.
shoreType
Indicates the kind or classification of a shoreline associated with a body of water or coastal area.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a6304e0c8190827fb57c5cac2da9 |
completed | March 1, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69a4a5004f708190a984ee221716e19c |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.