Triple
T3142012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Elizabeth National Park |
E65671
|
entity |
| Predicate | nearCity |
P350
|
FINISHED |
| Object |
Kasese
Kasese is a town in western Uganda that serves as a key gateway to Queen Elizabeth National Park and the Rwenzori Mountains.
|
E332728
|
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: Kasese | Statement: [Queen Elizabeth National Park, nearCity, Kasese]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kasese Context triple: [Queen Elizabeth National Park, nearCity, Kasese]
-
A.
Soroti
Soroti is a town in eastern Uganda that serves as a regional commercial and administrative center.
-
B.
Runyankole
Runyankole is a Bantu language spoken primarily by the Banyankole people in southwestern Uganda.
-
C.
Gwanda
Gwanda is a small Zimbabwean town that serves as an administrative and commercial hub in the country’s arid south, known historically for cattle ranching and gold mining.
-
D.
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.
-
E.
Kiryandongo District
Kiryandongo District is a central Ugandan district known for its agricultural communities and strategic location along major transport routes between Kampala and northern Uganda.
- 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: Kasese Triple: [Queen Elizabeth National Park, nearCity, Kasese]
Generated description
Kasese is a town in western Uganda that serves as a key gateway to Queen Elizabeth National Park and the Rwenzori Mountains.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kasese Target entity description: Kasese is a town in western Uganda that serves as a key gateway to Queen Elizabeth National Park and the Rwenzori Mountains.
-
A.
Soroti
Soroti is a town in eastern Uganda that serves as a regional commercial and administrative center.
-
B.
Runyankole
Runyankole is a Bantu language spoken primarily by the Banyankole people in southwestern Uganda.
-
C.
Gwanda
Gwanda is a small Zimbabwean town that serves as an administrative and commercial hub in the country’s arid south, known historically for cattle ranching and gold mining.
-
D.
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.
-
E.
Kiryandongo District
Kiryandongo District is a central Ugandan district known for its agricultural communities and strategic location along major transport routes between Kampala and northern Uganda.
- 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_69ad8582f564819088c27e1f96153938 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada579b07c8190a7b316f499911a2d |
completed | March 8, 2026, 4:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b224e4df38819089d0a11016a85ad8 |
completed | March 12, 2026, 2:28 a.m. |
| NEDg | Description generation | batch_69b228c1b568819088dc5ce4a15fedc2 |
completed | March 12, 2026, 2:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b22ccd34a8819089e207b6ee1f634a |
completed | March 12, 2026, 3:02 a.m. |
Created at: March 8, 2026, 3:05 p.m.