Triple
T5953945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parliament of Ghana |
E132465
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Accra |
E68377
|
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: Accra | Statement: [Parliament of Ghana, locatedIn, Accra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Accra Context triple: [Parliament of Ghana, locatedIn, Accra]
-
A.
Accra
chosen
Accra is the capital and largest city of Ghana, known as a major economic, political, and cultural hub in West Africa.
-
B.
Takoradi
Takoradi is a coastal city in southwestern Ghana that developed into a key commercial and industrial hub, particularly known for its deep-water seaport and role in regional trade.
-
C.
Kumasi
Kumasi is a major city in southern Ghana, known as the historic capital of the Ashanti Kingdom and a key cultural and commercial center in West Africa.
-
D.
Serekunda
Serekunda is the most populous urban center and a major commercial hub in The Gambia.
-
E.
Winneba, Ghana
Winneba, Ghana is a coastal town in the Central Region of Ghana known for its fishing industry, Aboakyer festival, and the University of Education, Winneba.
- 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_69c0086b05cc8190a8f36a96927a525c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c039bef5c8819093f280b235a593b0 |
completed | March 22, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0e3d77fb08190a24d319adc608df5 |
completed | March 23, 2026, 6:55 a.m. |
Created at: March 22, 2026, 4:02 p.m.