Triple
T16746690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volta Region |
E406973
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Kete Krachi |
E558200
|
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: Kete Krachi | Statement: [Volta Region, containsTown, Kete Krachi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kete Krachi Context triple: [Volta Region, containsTown, Kete Krachi]
-
A.
Kete Krachi
chosen
Kete Krachi is a town in the Oti Region of Ghana that serves as an important lakeside community and transport hub on the shores of Lake Volta.
-
B.
Kobina
Kobina is a Ghanaian given name commonly used for males born on a Tuesday.
-
C.
Kpɛlɛ
Kpɛlɛ is the endonym for the Kpelle language spoken by the Kpelle people of Liberia and Guinea.
-
D.
Kaneshie
Kaneshie is a bustling suburb of Accra, Ghana, known for its major transport hub and vibrant commercial activity.
-
E.
Ato Essandoh
Ato Essandoh is an American actor known for his work in film and television, including roles in series like "Vinyl" and "Altered Carbon" and films such as "Blood Diamond."
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3aa2311748190a17416de577ad159 |
completed | April 18, 2026, 3:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a52033748190ae207d72d437236b |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 5:21 a.m.