Triple
T16506123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nyarugenge District |
E400935
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Kanyinya Sector
Kanyinya Sector is an administrative sector within Kigali’s Nyarugenge District in Rwanda.
|
E1220176
|
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: Kanyinya Sector | Statement: [Nyarugenge District, contains, Kanyinya Sector]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kanyinya Sector Context triple: [Nyarugenge District, contains, Kanyinya Sector]
-
A.
Kacyiru sector
Kacyiru sector is an urban administrative area in Kigali, Rwanda, known for hosting many government institutions, embassies, and international organizations.
-
B.
Bumbogo sector
Bumbogo sector is an administrative subdivision of Gasabo District in Kigali, Rwanda, known for its semi-urban communities and agricultural activities.
-
C.
Kanombe sector
Kanombe sector is an urban administrative area in Kigali, Rwanda, known for hosting Kigali International Airport and several residential neighborhoods.
-
D.
Gikomero sector
Gikomero sector is an administrative subdivision of Gasabo District in Rwanda, encompassing rural communities and local governance structures.
-
E.
Nyarugunga sector
Nyarugunga sector is an urban administrative sector located within Kicukiro District in Kigali, Rwanda.
- 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: Kanyinya Sector Triple: [Nyarugenge District, contains, Kanyinya Sector]
Generated description
Kanyinya Sector is an administrative sector within Kigali’s Nyarugenge District in Rwanda.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kanyinya Sector Target entity description: Kanyinya Sector is an administrative sector within Kigali’s Nyarugenge District in Rwanda.
-
A.
Kacyiru sector
Kacyiru sector is an urban administrative area in Kigali, Rwanda, known for hosting many government institutions, embassies, and international organizations.
-
B.
Bumbogo sector
Bumbogo sector is an administrative subdivision of Gasabo District in Kigali, Rwanda, known for its semi-urban communities and agricultural activities.
-
C.
Kanombe sector
Kanombe sector is an urban administrative area in Kigali, Rwanda, known for hosting Kigali International Airport and several residential neighborhoods.
-
D.
Gikomero sector
Gikomero sector is an administrative subdivision of Gasabo District in Rwanda, encompassing rural communities and local governance structures.
-
E.
Nyarugunga sector
Nyarugunga sector is an urban administrative sector located within Kicukiro District in Kigali, Rwanda.
- 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_69d88381f6148190819958a038be990e |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e52a2b48190ae715e7db0fd3aad |
completed | April 18, 2026, 7:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0067a31c8881909b05c49c8006785d |
completed | May 10, 2026, 11:10 a.m. |
| NEDg | Description generation | batch_6a006bbe84b481908814dea1519bba84 |
completed | May 10, 2026, 11:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a006c0e8ff0819084b4b02b49db0386 |
completed | May 10, 2026, 11:29 a.m. |
Created at: April 10, 2026, 5:14 a.m.