Triple
T20354423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morogoro Region |
E496104
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Kilombero
Kilombero is a district and town in eastern Tanzania known for its fertile river valley, extensive rice farming, and rich biodiversity within the Morogoro Region.
|
E1425603
|
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: Kilombero | Statement: [Morogoro Region, containsCity, Kilombero]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kilombero Context triple: [Morogoro Region, containsCity, Kilombero]
-
A.
Kilembe
Kilembe is a town in western Uganda that serves as a common starting point for treks to the Rwenzori Mountains, including ascents of Margherita Peak.
-
B.
Lusikisiki
Lusikisiki is a small rural town in South Africa’s Eastern Cape, known for its scenic coastal surroundings and role as a local service and administrative center.
-
C.
Kasangati
Kasangati is a town in central Uganda that serves as a growing commercial and residential hub within the Greater Kampala metropolitan area.
-
D.
Mikongo
Mikongo is a small settlement in central Gabon that serves as a key access point for visitors exploring Lope National Park.
-
E.
Kibondo
Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
- 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: Kilombero Triple: [Morogoro Region, containsCity, Kilombero]
Generated description
Kilombero is a district and town in eastern Tanzania known for its fertile river valley, extensive rice farming, and rich biodiversity within the Morogoro Region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kilombero Target entity description: Kilombero is a district and town in eastern Tanzania known for its fertile river valley, extensive rice farming, and rich biodiversity within the Morogoro Region.
-
A.
Kilembe
Kilembe is a town in western Uganda that serves as a common starting point for treks to the Rwenzori Mountains, including ascents of Margherita Peak.
-
B.
Lusikisiki
Lusikisiki is a small rural town in South Africa’s Eastern Cape, known for its scenic coastal surroundings and role as a local service and administrative center.
-
C.
Kasangati
Kasangati is a town in central Uganda that serves as a growing commercial and residential hub within the Greater Kampala metropolitan area.
-
D.
Mikongo
Mikongo is a small settlement in central Gabon that serves as a key access point for visitors exploring Lope National Park.
-
E.
Kibondo
Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
- 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67852ca9881908a5af18005639859 |
completed | April 20, 2026, 7:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a086968a4d8819090d5fbb3229724f7 |
completed | May 16, 2026, 12:56 p.m. |
| NEDg | Description generation | batch_6a0869b998108190a5c6652c2f5f2f5d |
completed | May 16, 2026, 12:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a086a6812a08190b4594fa9b6054355 |
completed | May 16, 2026, 1 p.m. |
Created at: April 16, 2026, 11:25 a.m.