Triple
T8585720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buganda |
E203300
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Nakasongola |
E338918
|
NE 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: Nakasongola | Statement: [Buganda, contains, Nakasongola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nakasongola Context triple: [Buganda, contains, Nakasongola]
-
A.
Nakasongola
chosen
Nakasongola is a town in central Uganda that serves as an administrative and commercial center for the surrounding rural district.
-
B.
Kisoro
Kisoro is a small town in southwestern Uganda known as a gateway to gorilla trekking and the nearby Bwindi Impenetrable and Mgahinga Gorilla National Parks.
-
C.
Gokwe
Gokwe is a town in central Zimbabwe known for its cotton farming and role as a commercial hub in the Midlands Province.
-
D.
Monguno
Monguno is a town and local government area in Borno State, northeastern Nigeria, known for its strategic location and role in regional security dynamics.
-
E.
Kanyaga
"Kanyaga" is a popular Tanzanian Bongo Flava hit song by Diamond Platnumz known for its energetic beat and danceable style.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca8329bb7c8190a63c643730839103 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc457ab8b08190a53c730417288deb |
completed | March 31, 2026, 10:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf425243d8819084af0a789c73ea7c |
completed | April 3, 2026, 4:30 a.m. |
Created at: March 30, 2026, 6:22 p.m.