Triple
T1225293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sierra Leone |
E26313
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Freetown |
E70581
|
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: Freetown | Statement: [Sierra Leone, capital, Freetown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Freetown Context triple: [Sierra Leone, capital, Freetown]
-
A.
Freetown
chosen
Freetown is the capital and largest city of Sierra Leone, known as a historic port and former center for resettled freed slaves in West Africa.
-
B.
Monrovia
Monrovia is the largest city and main economic and administrative center of Liberia, located on the Atlantic coast in West Africa.
-
C.
Banjul
Banjul is the capital and principal port city of The Gambia, located on an island at the mouth of the Gambia River in West Africa.
-
D.
Accra
Accra is the capital and largest city of Ghana, known as a major economic, political, and cultural hub in West Africa.
-
E.
Conakry
Conakry is the capital and largest city of Guinea, serving as its main economic, cultural, and administrative center on the Atlantic coast of West Africa.
- 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_69a49484688c8190a1bf285eb396a8b6 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be382c4081909238c18b805352a7 |
completed | March 1, 2026, 10:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac8a0fcf508190be3668bd55f6f6d6 |
completed | March 7, 2026, 8:26 p.m. |
Created at: March 1, 2026, 7:47 p.m.