Triple
T7492661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shinyanga Region |
E177042
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Kigoma Region |
E5115
|
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: Kigoma Region | Statement: [Shinyanga Region, borders, Kigoma Region]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kigoma Region Context triple: [Shinyanga Region, borders, Kigoma Region]
-
A.
Kigoma Region
chosen
Kigoma Region is a western Tanzanian administrative region along Lake Tanganyika, known for its biodiversity and as a center for primate research.
-
B.
Rukwa Region
Rukwa Region is an administrative region in southwestern Tanzania known for its location along Lake Rukwa and its largely rural, agricultural economy.
-
C.
Iringa Region
Iringa Region is an administrative area in south-central Tanzania known for its highland landscapes and as the gateway to Ruaha National Park, one of the country’s largest wildlife reserves.
-
D.
Simiyu Region
Simiyu Region is an administrative region in northern Tanzania known for its predominantly rural economy based on agriculture and livestock.
-
E.
Kagera Region
Kagera Region is a northwestern region of Tanzania bordering Lake Victoria and several East African countries, known for its diverse ethnic groups, agriculture, and historical significance.
- 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_69c69f2583808190bd1a4936c42a5815 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5784c908190b701959daf082625 |
completed | March 27, 2026, 9:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c856acc3208190985e10c285f41e02 |
completed | March 28, 2026, 10:31 p.m. |
Created at: March 27, 2026, 3:43 p.m.