Triple
T4837668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dar es Salaam |
E108100
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Dar es Salaam Region |
E475392
|
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: Dar es Salaam Region | Statement: [Dar es Salaam, locatedIn, Dar es Salaam Region]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dar es Salaam Region Context triple: [Dar es Salaam, locatedIn, Dar es Salaam Region]
-
A.
Dar es Salaam Region
chosen
Dar es Salaam Region is a coastal administrative region in eastern Tanzania that encompasses the country’s largest city and main economic hub.
-
B.
Dodoma Region
Dodoma Region is an administrative region in central Tanzania that includes the national capital city, Dodoma.
-
C.
Rukwa Region
Rukwa Region is an administrative region in southwestern Tanzania known for its location along Lake Rukwa and its largely rural, agricultural economy.
-
D.
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.
-
E.
Arusha Region
Arusha Region is an administrative region in northern Tanzania known for its tourism hub city of Arusha and proximity to major national parks and Mount Kilimanjaro.
- 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_69bd43fbe444819085cb970706ef73f7 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ce2e810819089f9a3f2a7574d44 |
completed | March 20, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be67d449188190a2f02fa30aee4891 |
completed | March 21, 2026, 9:41 a.m. |
Created at: March 20, 2026, 1:25 p.m.