Triple
T18074099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lukiiko |
E432508
|
entity |
| Predicate | headquartersLocation |
P62
|
FINISHED |
| Object |
Mengo, Kampala
Mengo, Kampala is a historic neighborhood in Uganda’s capital city that serves as the traditional political and administrative center of the Buganda Kingdom.
|
E40695
|
NE FINISHED |
How this triple was built (4 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: Mengo, Kampala | Statement: [Lukiiko, headquartersLocation, Mengo, Kampala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mengo, Kampala Context triple: [Lukiiko, headquartersLocation, Mengo, Kampala]
-
A.
Kampala
Kampala is the capital and largest city of Uganda, serving as the country’s political, economic, and cultural center.
-
B.
Lyantonde
Lyantonde is a town and district in central Uganda, situated within the traditional kingdom region of Buganda.
-
C.
Nalubaale
Nalubaale is the traditional Luganda name for Lake Victoria, one of Africa’s Great Lakes and the world’s largest tropical lake.
-
D.
Kabete
Kabete is a prominent town in Kenya’s Central Region, situated within Kiambu County and known for its agricultural activity and proximity to Nairobi.
-
E.
Kalangala
Kalangala is a town on Uganda’s Ssese Islands in Lake Victoria, serving as the administrative and commercial center of Kalangala District.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mengo, Kampala Triple: [Lukiiko, headquartersLocation, Mengo, Kampala]
Generated description
Mengo, Kampala is a historic neighborhood in Uganda’s capital city that serves as the traditional political and administrative center of the Buganda Kingdom.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mengo, Kampala Target entity description: Mengo, Kampala is a historic neighborhood in Uganda’s capital city that serves as the traditional political and administrative center of the Buganda Kingdom.
-
A.
Kampala
chosen
Kampala is the capital and largest city of Uganda, serving as the country’s political, economic, and cultural center.
-
B.
Lyantonde
Lyantonde is a town and district in central Uganda, situated within the traditional kingdom region of Buganda.
-
C.
Nalubaale
Nalubaale is the traditional Luganda name for Lake Victoria, one of Africa’s Great Lakes and the world’s largest tropical lake.
-
D.
Kabete
Kabete is a prominent town in Kenya’s Central Region, situated within Kiambu County and known for its agricultural activity and proximity to Nairobi.
-
E.
Kalangala
Kalangala is a town on Uganda’s Ssese Islands in Lake Victoria, serving as the administrative and commercial center of Kalangala District.
- F. None of above.
Provenance (5 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ccefcdc4819086d0b224731bfc4d |
completed | April 19, 2026, 12:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a037c2f191c8190bd14af59689e57ab |
completed | May 12, 2026, 7:14 p.m. |
| NEDg | Description generation | batch_6a037cfd596481909d0c361a11185194 |
completed | May 12, 2026, 7:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a037e7bbd1c8190a88f57cdf5bf30f5 |
completed | May 12, 2026, 7:24 p.m. |
Created at: April 10, 2026, 10:26 a.m.