Triple
T14624777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Kariba |
E343316
|
entity |
| Predicate | hasNearbyTown |
P3883
|
FINISHED |
| Object | Binga |
E155418
|
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: Binga | Statement: [Lake Kariba, hasNearbyTown, Binga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Binga Context triple: [Lake Kariba, hasNearbyTown, Binga]
-
A.
Binga
chosen
Binga is a town and district in northwestern Zimbabwe known for its location on the southern shores of Lake Kariba and its association with the Tonga people.
-
B.
Yulu–Binga
Yulu–Binga is an alternative name for the Yulu language, a Central Sudanic language spoken in parts of Central Africa.
-
C.
Kabuna
Kabuna is a small village located on the atoll of Tabiteuea in the island nation of Kiribati in the central Pacific Ocean.
-
D.
Bwiro
Bwiro is a settlement located within Ukerewe District in Tanzania’s Mwanza Region.
-
E.
Mungaka
Mungaka is a Grassfields Bantu language spoken primarily in Cameroon, particularly associated with the Bamunka (Ndop) area.
- 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb468acc4819083b7e818d5cec809 |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda92a6b9c8190bdb220444cfbe34a |
completed | May 8, 2026, 9:13 a.m. |
Created at: April 10, 2026, 1:26 a.m.