Triple
T8367501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ama K. Abebrese |
E197169
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ama K. Abebrese |
E197169
|
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: Ama K. Abebrese | Statement: [Ama K. Abebrese, name, Ama K. Abebrese]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ama K. Abebrese Context triple: [Ama K. Abebrese, name, Ama K. Abebrese]
-
A.
Ama K. Abebrese
chosen
Ama K. Abebrese is a Ghanaian-British actress, television presenter, and producer known for her acclaimed performances in both African and international films.
-
B.
Cherisse Osei
Cherisse Osei is a British drummer best known for her work as the touring and recording drummer for the rock band Simple Minds.
-
C.
Nana Mensah
Nana Mensah is a Ghanaian-American actress, writer, and director known for her work in independent film and television, including a prominent role in the Netflix series "The Chair."
-
D.
Theodosia Okoh
Theodosia Okoh was a Ghanaian artist and teacher best known for creating Ghana’s national flag.
-
E.
Nana Aba Appiah Amfo
Nana Aba Appiah Amfo is a Ghanaian linguist and academic leader who serves as the Vice-Chancellor of the University of Ghana.
- 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_69ca82f2dbe48190aba982e75a0d94de |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb808e56fc81908b5d37482f29452d |
completed | March 31, 2026, 8:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cdc78c0c208190ba590c74512a4043 |
completed | April 2, 2026, 1:34 a.m. |
Created at: March 30, 2026, 6 p.m.