Triple
T8585701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buganda |
E203300
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Mpigi |
E744371
|
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: Mpigi | Statement: [Buganda, contains, Mpigi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mpigi Context triple: [Buganda, contains, Mpigi]
-
A.
Mpigi District
chosen
Mpigi District is an administrative district in central Uganda known for its agricultural activities and proximity to the capital, Kampala.
-
B.
Kasese
Kasese is a town in western Uganda that serves as a key gateway to Queen Elizabeth National Park and the Rwenzori Mountains.
-
C.
Nyanga District
Nyanga District is an administrative district in northeastern Zimbabwe known for its mountainous landscapes and popular tourist attractions such as Nyanga National Park.
-
D.
Rakai District
Rakai District is a rural administrative district in southern Uganda known for its agricultural economy and its early prominence in the country’s HIV/AIDS epidemic.
-
E.
Soroti
Soroti is a town in eastern Uganda that serves as a regional commercial and administrative center.
- 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_69cebb9716948190b0eb61ddf25fb333 |
completed | April 2, 2026, 6:55 p.m. |
Created at: March 30, 2026, 6:22 p.m.