Triple

T6077249
Position Surface form Disambiguated ID Type / Status
Subject West Region E135430 entity
Predicate hasMajorCity P316 FINISHED
Object Dschang
Dschang is a city in western Cameroon known as an important educational and cultural center, home to the University of Dschang and a mild highland climate.
 E567551 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: Dschang | Statement: [West Region, hasMajorCity, Dschang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dschang
Context triple: [West Region, hasMajorCity, Dschang]
  • A. Garki
    Garki is a prominent administrative and commercial district in Nigeria’s capital city, Abuja, housing numerous government offices, businesses, and residential areas.
  • B. Mambasa
    Mambasa is a town and administrative center located in the forested Ituri region of northeastern Democratic Republic of the Congo.
  • C. Njaba
    Njaba is a local government area in southeastern Nigeria known for its communities within Imo State and its role in local administration and commerce.
  • D. Chindau
    Chindau is a Bantu language spoken primarily by the Ndau people in parts of Mozambique and Zimbabwe.
  • E. Kumba
    Kumba is a major town in southwestern Cameroon known as a commercial hub and cultural crossroads where languages like Cameroonian Pidgin English are widely used.
  • 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: Dschang
Triple: [West Region, hasMajorCity, Dschang]
Generated description
Dschang is a city in western Cameroon known as an important educational and cultural center, home to the University of Dschang and a mild highland climate.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dschang
Target entity description: Dschang is a city in western Cameroon known as an important educational and cultural center, home to the University of Dschang and a mild highland climate.
  • A. Garki
    Garki is a prominent administrative and commercial district in Nigeria’s capital city, Abuja, housing numerous government offices, businesses, and residential areas.
  • B. Mambasa
    Mambasa is a town and administrative center located in the forested Ituri region of northeastern Democratic Republic of the Congo.
  • C. Njaba
    Njaba is a local government area in southeastern Nigeria known for its communities within Imo State and its role in local administration and commerce.
  • D. Chindau
    Chindau is a Bantu language spoken primarily by the Ndau people in parts of Mozambique and Zimbabwe.
  • E. Kumba
    Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
  • 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_69c11d48f0508190991453dc17c53b89 completed March 23, 2026, 11 a.m.
NEDg Description generation batch_69c11ed5a5748190b7320890397c8ce9 completed March 23, 2026, 11:07 a.m.
NED2 Entity disambiguation (via description) batch_69c11f34218c819094ce32eafff37489 completed March 23, 2026, 11:08 a.m.
Created at: March 22, 2026, 4:11 p.m.