Triple
T8585991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Kampala Hill |
E203306
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Nakasero Hill |
E203305
|
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: Nakasero Hill | Statement: [Old Kampala Hill, near, Nakasero Hill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nakasero Hill Context triple: [Old Kampala Hill, near, Nakasero Hill]
-
A.
Nakasero Hill
chosen
Nakasero Hill is an upscale, central neighborhood in Kampala known for hosting government offices, embassies, luxury hotels, and commercial centers.
-
B.
Kololo Hill
Kololo Hill is an upscale residential and diplomatic neighborhood in Kampala, Uganda, known for its embassies, luxury homes, and city views.
-
C.
Murahwa Hill
Murahwa Hill is a prominent historical and archaeological site near Mutare, Zimbabwe, known for its ancient rock shelters, rock art, and cultural significance to local communities.
-
D.
Kibuli Hill
Kibuli Hill is one of the prominent hills in Kampala, Uganda, known for its historic mosque and significant Muslim community institutions.
-
E.
Tama Hills
Tama Hills is a hilly, wooded area in western Tokyo and Kanagawa Prefecture known for its parks, residential neighborhoods, and natural landscapes on the outskirts of the Tokyo metropolitan region.
- 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_69cc457be9b88190bd9a2fc32350c31e |
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.