Triple
T7794632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nzega |
E180267
|
entity |
| Predicate | roadConnection |
P385
|
FINISHED |
| Object | Shinyanga |
E177042
|
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: Shinyanga | Statement: [Nzega, roadConnection, Shinyanga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shinyanga Context triple: [Nzega, roadConnection, Shinyanga]
-
A.
Shinyanga Region
chosen
Shinyanga Region is an administrative region in northwestern Tanzania known for its agriculture, mining activities, and proximity to Lake Victoria.
-
B.
Nyamwezi
Nyamwezi is a Bantu language spoken primarily in northwestern Tanzania by the Nyamwezi people.
-
C.
Nyanga
Nyanga is a township on the Cape Flats near Cape Town, South Africa, known for its history of apartheid-era resistance and ongoing social and economic challenges.
-
D.
Soroti
Soroti is a town in eastern Uganda that serves as a regional commercial and administrative center.
-
E.
Kasese
Kasese is a town in western Uganda that serves as a key gateway to Queen Elizabeth National Park and the Rwenzori Mountains.
- 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_69ca827d22208190b4dc5aa680edcf5d |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cae93b262c8190b55e5ab2bc72d894 |
completed | March 30, 2026, 9:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5a0a34fc81908e7852ed0dbc377c |
completed | March 31, 2026, 5:22 a.m. |
Created at: March 30, 2026, 4:31 p.m.