Triple

T10400664
Position Surface form Disambiguated ID Type / Status
Subject Ngounié Province E245136 entity
Predicate hasSettlement P1068 FINISHED
Object Ndendé
Ndendé is a town in southern Gabon that serves as an important local center within Ngounié Province.
 E863729 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: Ndendé | Statement: [Ngounié Province, hasSettlement, Ndendé]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ndendé
Context triple: [Ngounié Province, hasSettlement, Ndendé]
  • A. Ndé
    Ndé is an administrative division (department) located in Cameroon's West Region, known for its predominantly Bamiléké population and highland rural communities.
  • B. Ndiass
    Ndiass is a village in western Senegal that serves as the host community for Blaise Diagne International Airport, one of the country’s main air transport hubs.
  • C. Ndowe
    Ndowe is a Bantu language spoken by the Ndowe people along the coastal region of Equatorial Guinea.
  • D. Ngazidja
    Ngazidja, also known as Grande Comore, is the largest island of the Comoros archipelago in the Indian Ocean and home to the nation’s capital.
  • E. Ntem
    Ntem is a town located in the South Region of Cameroon.
  • 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: Ndendé
Triple: [Ngounié Province, hasSettlement, Ndendé]
Generated description
Ndendé is a town in southern Gabon that serves as an important local center within Ngounié Province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ndendé
Target entity description: Ndendé is a town in southern Gabon that serves as an important local center within Ngounié Province.
  • A. Ndé
    Ndé is an administrative division (department) located in Cameroon's West Region, known for its predominantly Bamiléké population and highland rural communities.
  • B. Ndiass
    Ndiass is a village in western Senegal that serves as the host community for Blaise Diagne International Airport, one of the country’s main air transport hubs.
  • C. Ndowe
    Ndowe is a Bantu language spoken by the Ndowe people along the coastal region of Equatorial Guinea.
  • D. Ngazidja
    Ngazidja, also known as Grande Comore, is the largest island of the Comoros archipelago in the Indian Ocean and home to the nation’s capital.
  • E. Ntem
    Ntem is a town located in the South Region of Cameroon.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9e2f11c8190b30695cba2975544 completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d87e84f7a08190b83ecfec72efb7a7 completed April 10, 2026, 4:37 a.m.
NEDg Description generation batch_69d886c325c4819089dac35eb26e7961 completed April 10, 2026, 5:12 a.m.
NED2 Entity disambiguation (via description) batch_69d88dbbe97c8190861e08f3ff39f91b completed April 10, 2026, 5:42 a.m.
Created at: April 6, 2026, 12:07 p.m.