Triple
T13054268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nyanga District |
E327528
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Nyanga town |
E1020680
|
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: Nyanga town | Statement: [Nyanga District, contains, Nyanga town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nyanga town Context triple: [Nyanga District, contains, Nyanga town]
-
A.
Nyanga District
Nyanga District is an administrative district in northeastern Zimbabwe known for its mountainous landscapes and popular tourist attractions such as Nyanga National Park.
-
B.
Lyantonde
Lyantonde is a town and district in central Uganda, situated within the traditional kingdom region of Buganda.
-
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.
Nyanga
chosen
Nyanga is a town and popular tourist destination in eastern Zimbabwe, known for its scenic highlands, national park, and proximity to major waterfalls and mountain landscapes.
-
E.
Kisumu
Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980bb52d88190b5be12000e27a2c9 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6f5c771fc8190afb6b0f449c67294 |
completed | May 3, 2026, 7:14 a.m. |
Created at: April 9, 2026, 8:58 p.m.