Triple
T22047375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruvuma Region |
E544796
|
entity |
| Predicate | bordersWith |
P224
|
FINISHED |
| Object | Lindi Region |
—
|
NE NERFINISHED |
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: Lindi Region | Statement: [Ruvuma Region, bordersWith, Lindi Region]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lindi Region Context triple: [Ruvuma Region, bordersWith, Lindi Region]
-
A.
Lindi Region
chosen
Lindi Region is a coastal administrative region in southern Tanzania known for its historical Swahili settlements and Indian Ocean shoreline.
-
B.
Ruvuma Region
Ruvuma Region is a largely rural administrative area in southern Tanzania known for its wildlife, forests, and proximity to major conservation areas.
-
C.
Kunene Region
Kunene Region is a sparsely populated, northwestern region of Namibia known for its rugged landscapes, desert-adapted wildlife, and remote Atlantic coastline.
-
D.
Omaheke Region
Omaheke Region is an administrative region in eastern Namibia known for its semi-arid savannah landscapes and cattle farming.
-
E.
Negombo region
The Negombo region is a coastal area in western Sri Lanka known for its fishing industry, beaches, and proximity to the country’s main international airport.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e32445c8190ab97089b48a130bb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12830c674819080254d77ee02bc9f |
completed | April 28, 2026, 9:35 p.m. |
Created at: April 16, 2026, 8:26 p.m.