Triple
T13804645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Region of Uganda |
E331727
|
entity |
| Predicate | hasUrbanCenter |
P2106
|
FINISHED |
| Object |
Malaba
Malaba is a key border town between Uganda and Kenya that serves as a major transit point for regional trade and transport.
|
E1061856
|
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: Malaba | Statement: [Eastern Region of Uganda, hasUrbanCenter, Malaba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malaba Context triple: [Eastern Region of Uganda, hasUrbanCenter, Malaba]
-
A.
Kapiri Mposhi
Kapiri Mposhi is a town in central Zambia that serves as a key rail and road junction linking the country to Tanzania and other regions.
-
B.
Manzini
Manzini is a major city in Eswatini that serves as an important commercial and transport hub of the country.
-
C.
Matadi
Matadi is a major port city in western Democratic Republic of the Congo, serving as the country’s principal seaport and a key gateway for trade between the Atlantic Ocean and the interior via the Congo River.
-
D.
Chegutu
Chegutu is a town in central northern Zimbabwe known for its agricultural activities and gold mining.
-
E.
Masindi
Masindi is a town in western Uganda that serves as a key gateway and service center for visitors to Murchison Falls National Park.
- 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: Malaba Triple: [Eastern Region of Uganda, hasUrbanCenter, Malaba]
Generated description
Malaba is a key border town between Uganda and Kenya that serves as a major transit point for regional trade and transport.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Malaba Target entity description: Malaba is a key border town between Uganda and Kenya that serves as a major transit point for regional trade and transport.
-
A.
Kapiri Mposhi
Kapiri Mposhi is a town in central Zambia that serves as a key rail and road junction linking the country to Tanzania and other regions.
-
B.
Manzini
Manzini is a major city in Eswatini that serves as an important commercial and transport hub of the country.
-
C.
Matadi
Matadi is a major port city in western Democratic Republic of the Congo, serving as the country’s principal seaport and a key gateway for trade between the Atlantic Ocean and the interior via the Congo River.
-
D.
Chegutu
Chegutu is a town in central northern Zimbabwe known for its agricultural activities and gold mining.
-
E.
Masindi
Masindi is a town in western Uganda that serves as a key gateway and service center for visitors to Murchison Falls National Park.
- F. None of above. chosen
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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de026c36108190a7436034a730a261 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b08db39c8190a76637b36b77d643 |
completed | May 3, 2026, 8:31 p.m. |
| NEDg | Description generation | batch_69f7b18bbe688190855a26b8f2b4bcc0 |
completed | May 3, 2026, 8:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7b260fc6c8190a573cc525388878e |
completed | May 3, 2026, 8:38 p.m. |
Created at: April 9, 2026, 10:12 p.m.