Triple
T26047943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L'Agulhas |
E647883
|
entity |
| Predicate | hasNearbyOceanCurrent |
P117087
|
FINISHED |
| Object | Agulhas Current |
—
|
NE NERFINISHED |
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: Agulhas Current | Statement: [L'Agulhas, hasNearbyOceanCurrent, Agulhas Current]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyOceanCurrent Context triple: [L'Agulhas, hasNearbyOceanCurrent, Agulhas Current]
-
A.
oceanCurrentsMeetNear
Indicates that two or more ocean currents converge or come into close proximity in a particular area.
-
B.
hasNearbyMarineFeature
chosen
Indicates that one entity is located close to a marine geographic feature associated with the other entity.
-
C.
hasNearbyCoast
Indicates that one location is situated close to a coastline or seashore.
-
D.
oceanCurrent
Indicates the flow of seawater in a consistent direction driven by factors like wind, temperature, and salinity.
-
E.
hasNearbyWater
Indicates that one entity is located close to a body of water associated with or relevant to another entity.
- 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_69e77e8d419481908004e6318d28aaab |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 22, 2026, 9:10 a.m.