Triple

T6077241
Position Surface form Disambiguated ID Type / Status
Subject West Region E135430 entity
Predicate hasDepartment P35 FINISHED
Object Haut-Nkam
Haut-Nkam is an administrative department in western Cameroon known for its mix of highland landscapes, agriculture, and small urban centers.
E565689 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: Haut-Nkam | Statement: [West Region, hasDepartment, Haut-Nkam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haut-Nkam
Context triple: [West Region, hasDepartment, Haut-Nkam]
  • A. Kié-Ntem
    Kié-Ntem is a province in mainland Equatorial Guinea known for its largely forested landscapes and border location with Cameroon and Gabon.
  • B. Ngounié Province
    Ngounié Province is an inland administrative region in southwestern Gabon known for its forests, rivers, and ethnolinguistic diversity.
  • C. Etung
    Etung is a local government area in southeastern Nigeria known for its diverse communities and agricultural activities within Cross River State.
  • D. 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.
  • E. Aboh Mbaise
    Aboh Mbaise is a local government area in southeastern Nigeria known for its predominantly Igbo population and rich cultural traditions.
  • 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: Haut-Nkam
Triple: [West Region, hasDepartment, Haut-Nkam]
Generated description
Haut-Nkam is an administrative department in western Cameroon known for its mix of highland landscapes, agriculture, and small urban centers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Haut-Nkam
Target entity description: Haut-Nkam is an administrative department in western Cameroon known for its mix of highland landscapes, agriculture, and small urban centers.
  • A. Kié-Ntem
    Kié-Ntem is a province in mainland Equatorial Guinea known for its largely forested landscapes and border location with Cameroon and Gabon.
  • B. Ngounié Province
    Ngounié Province is an inland administrative region in southwestern Gabon known for its forests, rivers, and ethnolinguistic diversity.
  • C. Etung
    Etung is a local government area in southeastern Nigeria known for its diverse communities and agricultural activities within Cross River State.
  • D. 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.
  • E. Aboh Mbaise
    Aboh Mbaise is a local government area in southeastern Nigeria known for its predominantly Igbo population and rich cultural traditions.
  • 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_69c0087ad31c8190ab936e0ff28614b6 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0576ef2c88190b0ec62e9f041d176 completed March 22, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11d43f7908190845c2337cd243a3c completed March 23, 2026, 11 a.m.
NEDg Description generation batch_69c11db0b62c81908584215a5092a7a8 completed March 23, 2026, 11:02 a.m.
NED2 Entity disambiguation (via description) batch_69c11e4685d08190ac97e2356e64527e completed March 23, 2026, 11:04 a.m.
Created at: March 22, 2026, 4:11 p.m.