Triple
T5948131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Region (Cameroon) |
E132329
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Lagdo
Lagdo is a town in northern Cameroon known for its large hydroelectric dam on the Benue River and the resulting Lagdo Reservoir.
|
E557641
|
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: Lagdo | Statement: [North Region (Cameroon), containsCity, Lagdo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lagdo Context triple: [North Region (Cameroon), containsCity, Lagdo]
-
A.
Khorab
Khorab is a historic site in present-day Namibia known as the location where German colonial forces surrendered to South African troops during the South-West Africa Campaign of World War I.
-
B.
Terevaka
Terevaka is a large extinct volcanic peak that forms the highest and youngest of the three main volcanoes making up Easter Island.
-
C.
Cayor
Cayor was a precolonial Wolof kingdom in what is now Senegal, emerging as a major regional power after the decline of the Wolof Empire.
-
D.
Landana
Landana is a coastal town in Angola’s Cabinda exclave, historically known as a regional trading and missionary center.
-
E.
Mouraria
Mouraria is a historic Lisbon neighborhood known for its multicultural character, narrow medieval streets, and deep ties to traditional fado music.
- 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: Lagdo Triple: [North Region (Cameroon), containsCity, Lagdo]
Generated description
Lagdo is a town in northern Cameroon known for its large hydroelectric dam on the Benue River and the resulting Lagdo Reservoir.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lagdo Target entity description: Lagdo is a town in northern Cameroon known for its large hydroelectric dam on the Benue River and the resulting Lagdo Reservoir.
-
A.
Khorab
Khorab is a historic site in present-day Namibia known as the location where German colonial forces surrendered to South African troops during the South-West Africa Campaign of World War I.
-
B.
Terevaka
Terevaka is a large extinct volcanic peak that forms the highest and youngest of the three main volcanoes making up Easter Island.
-
C.
Cayor
Cayor was a precolonial Wolof kingdom in what is now Senegal, emerging as a major regional power after the decline of the Wolof Empire.
-
D.
Landana
Landana is a coastal town in Angola’s Cabinda exclave, historically known as a regional trading and missionary center.
-
E.
Mouraria
Mouraria is a historic Lisbon neighborhood known for its multicultural character, narrow medieval streets, and deep ties to traditional fado music.
- 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_69c00869d3308190af89b2453e0f7546 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0397c80708190a4778fdb353314b7 |
completed | March 22, 2026, 6:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c08d4f0481908547609bc2736380 |
completed | March 23, 2026, 4:24 a.m. |
| NEDg | Description generation | batch_69c0c19665b08190ab3c66b7c6c33f61 |
completed | March 23, 2026, 4:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0c4576824819080ced71df8fdda6c |
completed | March 23, 2026, 4:40 a.m. |
Created at: March 22, 2026, 4:01 p.m.