Triple
T10059000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mwanza Region |
E208934
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Mwanza City |
E813769
|
NE FINISHED |
How this triple was built (2 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: Mwanza City | Statement: [Mwanza Region, contains, Mwanza City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mwanza City Context triple: [Mwanza Region, contains, Mwanza City]
-
A.
Mwanza city
chosen
Mwanza city is a major urban and commercial center on the southern shores of Lake Victoria in northern Tanzania, known for its port, fishing industry, and role as a regional hub.
-
B.
Mvumbi
Mvumbi is the Zulu name of Albert Luthuli, the South African anti-apartheid leader and Nobel Peace Prize laureate.
-
C.
Orangi Town
Orangi Town is a densely populated residential area in Karachi, Pakistan, known as one of Asia’s largest informal settlements.
-
D.
Oshakati
Oshakati is a major northern Namibian town that serves as an important commercial and administrative hub.
-
E.
Egoli
Egoli is a common nickname for Johannesburg, South Africa’s major economic hub often referred to as the "City of Gold."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca836094408190a36a1ea7e9a86fcd |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcfb0f17c8190a8c0cfb02863537d |
completed | April 2, 2026, 2:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b624191c819093b8392b5573fa96 |
completed | April 5, 2026, 7:21 p.m. |
Created at: March 30, 2026, 8:57 p.m.