Triple
T10543034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haut-Ogooué Province |
E248743
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Moanda
Moanda is a major mining town in southeastern Gabon known for its rich manganese deposits and role in the country’s extractive industry.
|
E871351
|
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: Moanda | Statement: [Haut-Ogooué Province, containsCity, Moanda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moanda Context triple: [Haut-Ogooué Province, containsCity, Moanda]
-
A.
Butembo
Butembo is a major commercial city in eastern Democratic Republic of the Congo, known as a trading hub and economic center in North Kivu.
-
B.
Ekondo-Titi
Ekondo-Titi is a coastal town and commune in Cameroon's Southwest Region, known for its agricultural activities and location near the Ndian River and the Atlantic coast.
-
C.
Benina
Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
-
D.
Lambaréné
Lambaréné is a town in western Gabon best known for its location on the Ogooué River and for hosting the historic Albert Schweitzer Hospital.
-
E.
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.
- 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: Moanda Triple: [Haut-Ogooué Province, containsCity, Moanda]
Generated description
Moanda is a major mining town in southeastern Gabon known for its rich manganese deposits and role in the country’s extractive industry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Moanda Target entity description: Moanda is a major mining town in southeastern Gabon known for its rich manganese deposits and role in the country’s extractive industry.
-
A.
Butembo
Butembo is a major commercial city in eastern Democratic Republic of the Congo, known as a trading hub and economic center in North Kivu.
-
B.
Ekondo-Titi
Ekondo-Titi is a coastal town and commune in Cameroon's Southwest Region, known for its agricultural activities and location near the Ndian River and the Atlantic coast.
-
C.
Benina
Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
-
D.
Lambaréné
Lambaréné is a town in western Gabon best known for its location on the Ogooué River and for hosting the historic Albert Schweitzer Hospital.
-
E.
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.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5190f46d08190a92b1191881ffb92 |
completed | April 7, 2026, 2:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9342e6cf48190b0ca53ff2a4e0214 |
completed | April 10, 2026, 5:32 p.m. |
| NEDg | Description generation | batch_69d938c697f481908a93296ee7f82eae |
completed | April 10, 2026, 5:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d940176c988190b7583ce9f2c21898 |
completed | April 10, 2026, 6:23 p.m. |
Created at: April 6, 2026, 12:32 p.m.