Triple
T11574380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Region, Ghana |
E274465
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Komenda |
E599442
|
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: Komenda | Statement: [Central Region, Ghana, contains, Komenda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Komenda Context triple: [Central Region, Ghana, contains, Komenda]
-
A.
Komenda
chosen
Komenda is a coastal town in Ghana’s Central Region historically known as an important Fante trading and fishing center.
-
B.
Chindau
Chindau is a Bantu language spoken primarily by the Ndau people in parts of Mozambique and Zimbabwe.
-
C.
Soshanguve
Soshanguve is a large township in the northern part of the Gauteng province of South Africa, known for its diverse population and proximity to Pretoria.
-
D.
Moanda
Moanda is a major mining town in southeastern Gabon known for its rich manganese deposits and role in the country’s extractive industry.
-
E.
Nakonde
Nakonde is a town in northeastern Zambia near the border with Tanzania, serving as a key border crossing and trade hub between the two countries.
- 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_69d6aae5ac3c81908d2b0a3a665665b2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d89048120c81908258f984711f7dd4 |
completed | April 10, 2026, 5:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e713e49f508190b9bad316d68eab42 |
completed | April 21, 2026, 6:06 a.m. |
Created at: April 8, 2026, 9:38 p.m.