Triple
T20354383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Tanzania |
E496103
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Ruvuma 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: Ruvuma Region | Statement: [Southern Tanzania, contains, Ruvuma Region]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruvuma Region Context triple: [Southern Tanzania, contains, Ruvuma Region]
-
A.
Ruvuma Region
chosen
Ruvuma Region is a largely rural administrative area in southern Tanzania known for its wildlife, forests, and proximity to major conservation areas.
-
B.
Lindi Region
Lindi Region is a coastal administrative region in southern Tanzania known for its historical Swahili settlements and Indian Ocean shoreline.
-
C.
Vumba region
The Vumba region is a scenic highland area in eastern Zimbabwe known for its lush forests, cool misty climate, and rich biodiversity, attracting nature lovers and tourists.
-
D.
Mafinga region
Mafinga Region is an administrative area in Tanzania that includes Mafinga Central and surrounding localities.
-
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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67852ca9881908a5af18005639859 |
completed | April 20, 2026, 7:02 p.m. |
Created at: April 16, 2026, 11:25 a.m.