Triple
T2171127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agulhas Current |
E48426
|
entity |
| Predicate | hasTypicalWaterMass |
P6126
|
FINISHED |
| Object | Subtropical Surface Water |
—
|
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 Surface Water | Statement: [Agulhas Current, hasTypicalWaterMass, Subtropical Surface Water]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalWaterMass Context triple: [Agulhas Current, hasTypicalWaterMass, Subtropical Surface Water]
-
A.
includesWaterMass
Indicates that one entity contains, encompasses, or has within its boundaries a body or mass of water.
-
B.
waterMassType
chosen
Indicates the classification of a body of water according to its physical or compositional type.
-
C.
waterMassProperty
Indicates a relationship where a specific physical or chemical property is attributed to a body or mass of water.
-
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.
waterMassInfluence
Indicates how the presence, amount, or distribution of water mass affects or modifies another entity or system.
- 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc1559ff481908efe3f214b2570dc |
completed | March 7, 2026, 6:10 a.m. |
| PD | Predicate disambiguation | batch_69abbd9efc1c81909a65044a1ffc9038 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.