Triple
T20354424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morogoro Region |
E496104
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Mvomero
Mvomero is a district and rural town in eastern Tanzania known for its agricultural activities within the Morogoro Region.
|
E1424820
|
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: Mvomero | Statement: [Morogoro Region, containsCity, Mvomero]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mvomero Context triple: [Morogoro Region, containsCity, Mvomero]
-
A.
Mqanduli
Mqanduli is a small town in South Africa’s Eastern Cape province, situated in a rural area historically associated with the Xhosa people.
-
B.
Mambo
Mambo is an open-source content management system that was widely used in the early 2000s for building dynamic websites and later served as the codebase origin for Joomla!.
-
C.
Mambo
Mambo was the royal title used for the supreme ruler of the Rozvi Empire in what is now Zimbabwe.
-
D.
Kwa Ngwaru
"Kwa Ngwaru" is a popular Bongo Flava song by Tanzanian artist Harmonize, known for its catchy melody and widespread acclaim in East Africa.
-
E.
Mishanya
Mishanya is a Russian diminutive nickname commonly used for the male given name Mikhail.
- 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: Mvomero Triple: [Morogoro Region, containsCity, Mvomero]
Generated description
Mvomero is a district and rural town in eastern Tanzania known for its agricultural activities within the Morogoro Region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mvomero Target entity description: Mvomero is a district and rural town in eastern Tanzania known for its agricultural activities within the Morogoro Region.
-
A.
Mqanduli
Mqanduli is a small town in South Africa’s Eastern Cape province, situated in a rural area historically associated with the Xhosa people.
-
B.
Mambo
Mambo is an open-source content management system that was widely used in the early 2000s for building dynamic websites and later served as the codebase origin for Joomla!.
-
C.
Mambo
Mambo was the royal title used for the supreme ruler of the Rozvi Empire in what is now Zimbabwe.
-
D.
Kwa Ngwaru
"Kwa Ngwaru" is a popular Bongo Flava song by Tanzanian artist Harmonize, known for its catchy melody and widespread acclaim in East Africa.
-
E.
Mishanya
Mishanya is a Russian diminutive nickname commonly used for the male given name Mikhail.
- 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_6a086a6ad6c88190be1770758d2e1bbf |
completed | May 16, 2026, 1 p.m. |
Created at: April 16, 2026, 11:25 a.m.