Triple
T5992201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Region (Cameroon) |
E133375
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Abong-Mbang
Abong-Mbang is a town in eastern Cameroon that serves as a local administrative and commercial center in the East Region.
|
E562009
|
NE FINISHED |
How this triple was built (4 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: Abong-Mbang | Statement: [East Region (Cameroon), containsTown, Abong-Mbang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abong-Mbang Context triple: [East Region (Cameroon), containsTown, Abong-Mbang]
-
A.
Dutsin-Ma
Dutsin-Ma is a town in northern Nigeria known for hosting the Federal University Dutsin-Ma and serving as an important local commercial and educational center.
-
B.
Benina
Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
-
C.
Ubangi-Shari
Ubangi-Shari was the French colonial territory in central Africa that later became the independent nation of the Central African Republic.
-
D.
Oshindonga
Oshindonga is a standardized Bantu language variety spoken primarily in northern Namibia and southern Angola, forming one of the main dialects of the Oshiwambo language cluster.
-
E.
Ebanga
Ebanga is a monoclonal antibody drug used to treat Zaire ebolavirus infection (Ebola virus disease).
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Abong-Mbang Triple: [East Region (Cameroon), containsTown, Abong-Mbang]
Generated description
Abong-Mbang is a town in eastern Cameroon that serves as a local administrative and commercial center in the East Region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Abong-Mbang Target entity description: Abong-Mbang is a town in eastern Cameroon that serves as a local administrative and commercial center in the East Region.
-
A.
Dutsin-Ma
Dutsin-Ma is a town in northern Nigeria known for hosting the Federal University Dutsin-Ma and serving as an important local commercial and educational center.
-
B.
Benina
Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
-
C.
Ubangi-Shari
Ubangi-Shari was the French colonial territory in central Africa that later became the independent nation of the Central African Republic.
-
D.
Oshindonga
Oshindonga is a standardized Bantu language variety spoken primarily in northern Namibia and southern Angola, forming one of the main dialects of the Oshiwambo language cluster.
-
E.
Ebanga
Ebanga is a monoclonal antibody drug used to treat Zaire ebolavirus infection (Ebola virus disease).
- F. None of above. chosen
Provenance (5 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_69c0087010d081908bb8142342d63330 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04e8fd030819095a4f3b3d425ec21 |
completed | March 22, 2026, 8:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c108685f788190aa3f84e56837b195 |
completed | March 23, 2026, 9:31 a.m. |
| NEDg | Description generation | batch_69c10a15b9e08190be8b559e467d1d8c |
completed | March 23, 2026, 9:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c10aaf299481909d0e824a126381e3 |
completed | March 23, 2026, 9:41 a.m. |
Created at: March 22, 2026, 4:05 p.m.