Triple
T2315032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salé |
E51043
|
entity |
| Predicate | riverMouthNearby |
P8567
|
FINISHED |
| Object | Bou Regreg River mouth |
—
|
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: Bou Regreg River mouth | Statement: [Salé, riverMouthNearby, Bou Regreg River mouth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riverMouthNearby Context triple: [Salé, riverMouthNearby, Bou Regreg River mouth]
-
A.
hasEstuaryNear
Indicates that the estuary of a water body is located in close proximity to a specified place or feature.
-
B.
mouthOfTheWatercourse
Indicates the location where a watercourse ends and flows into a larger body of water.
-
C.
mouthOfWatercourse
Indicates the location where a watercourse ends and flows into a larger body of water or another watercourse.
-
D.
nearbyWatercourse
chosen
Indicates that one entity is located close to or alongside a natural or artificial watercourse, such as a river, stream, or canal.
-
E.
estuaryName
Indicates the naming relationship that assigns a specific name to an estuary.
- 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_69a88b074b908190ae983dbca7757d88 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc58e88e481908733fdf79d3f8a15 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.