Triple
T13054147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mutasa |
E327525
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Mutasa District |
E327526
|
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: Mutasa District | Statement: [Mutasa, locatedIn, Mutasa District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mutasa District Context triple: [Mutasa, locatedIn, Mutasa District]
-
A.
Mutasa District
chosen
Mutasa District is an administrative district in eastern Zimbabwe known for its mountainous terrain, tea and coffee estates, and location within Manicaland Province.
-
B.
Buhera District
Buhera District is an administrative district in eastern Zimbabwe known for its rural communities and agricultural activities.
-
C.
Ilemela District
Ilemela District is an administrative district and urban area within Tanzania’s Mwanza Region, encompassing part of the city of Mwanza along the shores of Lake Victoria.
-
D.
Montaza district
Montaza district is a coastal area in Alexandria, Egypt, known for its expansive royal gardens, beaches, and historic palaces.
-
E.
Magu District
Magu District is an administrative district in northern Tanzania, located within the Mwanza Region along the southern shores of Lake Victoria.
- 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_69f716baf00881909a1a11d36cdb8d42 |
completed | May 3, 2026, 9:34 a.m. |
Created at: April 9, 2026, 8:58 p.m.