Triple
T20628003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lugazi |
E506870
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | River Sezibwa |
—
|
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: River Sezibwa | Statement: [Lugazi, near, River Sezibwa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: River Sezibwa Context triple: [Lugazi, near, River Sezibwa]
-
A.
Sezibwa River
chosen
The Sezibwa River is a culturally significant river in central Uganda, known for its scenic waterfalls and traditional spiritual importance to local communities.
-
B.
Mgwali River
The Mgwali River is a tributary watercourse in South Africa that feeds into the larger Mbashe River system.
-
C.
Kwisa River
The Kwisa River is a river in southwestern Poland that flows through the historical region of Lower Silesia before joining the Bóbr River.
-
D.
Umbilo River
The Umbilo River is a watercourse in KwaZulu-Natal, South Africa, that flows through the Durban area before entering the Indian Ocean.
-
E.
Awali River
The Awali River is a significant watercourse in Lebanon that flows through the region of Sidon before emptying into the Mediterranean Sea.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4bd4a0081908d4e97a590a33fb2 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abe645888190b639ebedc5b3041a |
completed | April 20, 2026, 10:42 p.m. |
Created at: April 16, 2026, 11:42 a.m.