Triple
T6208984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuroshio–Oyashio confluence region |
E138818
|
entity |
| Predicate | hasWaterMassSource |
P65385
|
FINISHED |
| Object | subtropical waters |
—
|
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: subtropical waters | Statement: [Kuroshio–Oyashio confluence region, hasWaterMassSource, subtropical waters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterMassSource Context triple: [Kuroshio–Oyashio confluence region, hasWaterMassSource, subtropical waters]
-
A.
hasWaterMassOrigin
chosen
Indicates that something originates from, or is derived from, a particular body or mass of water.
-
B.
includesWaterMass
Indicates that one entity contains, encompasses, or has within its boundaries a body or mass of water.
-
C.
hasWaterResourceType
Indicates that an entity is associated with a specific type or category of water resource.
-
D.
hasHydrosphere
Indicates that an entity possesses or is characterized by a surrounding layer or system of water, such as oceans, seas, lakes, or other bodies of liquid water.
-
E.
hasWaterFeatures
Indicates that an entity includes or is associated with water-related elements such as fountains, ponds, streams, or similar features.
- 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_69c008ada364819096c9e92c74d639b5 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0628850bc819080a26c5e05a1d29f |
completed | March 22, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69c055fdea3c81908f5d910f0d36234a |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:21 p.m.