Triple
T13593335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chipinge |
E324746
|
entity |
| Predicate | hasNearbyTown |
P3883
|
FINISHED |
| Object | Chiredzi |
E402285
|
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: Chiredzi | Statement: [Chipinge, hasNearbyTown, Chiredzi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chiredzi Context triple: [Chipinge, hasNearbyTown, Chiredzi]
-
A.
Chiredzi
chosen
Chiredzi is a town in southeastern Zimbabwe known as a center for sugarcane farming and a gateway to nearby wildlife and conservation areas.
-
B.
Cedza
Cedza is a Swazi prince and social entrepreneur known for his work in youth leadership and development initiatives.
-
C.
Sinazongwe
Sinazongwe is a lakeside town in southern Zambia situated on the shores of Lake Kariba, known primarily for fishing and agriculture.
-
D.
Kasena
Kasena is a Gur language spoken primarily by the Kasena people in northern Ghana and southern Burkina Faso.
-
E.
Tongayi
Tongayi is a Zimbabwean actor known for his roles in film and television, including appearances in international productions.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb057f1c881909a3bb77c659a724a |
completed | April 12, 2026, 2:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76bc578908190abd5cca94b1c3a5c |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.