Triple

T6435990
Position Surface form Disambiguated ID Type / Status
Subject Southwest Region (Cameroon) E129895 entity
Predicate containsCity P294 FINISHED
Object Mamfe
Mamfe is a town in western Cameroon known as an important local trade and transport hub near the Nigerian border.
E595838 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: Mamfe | Statement: [Southwest Region (Cameroon), containsCity, Mamfe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mamfe
Context triple: [Southwest Region (Cameroon), containsCity, Mamfe]
  • A. Mumuye
    The Mumuye are an indigenous ethnic group of northeastern Nigeria known for their distinct language and rich artistic traditions, particularly their stylized wooden sculptures.
  • B. Majene
    Majene is a coastal town and regency capital in West Sulawesi, Indonesia, known for its fishing industry and role as a regional administrative center.
  • C. Mwotlap
    Mwotlap is an Oceanic Austronesian language spoken on Mota Lava and nearby islands in northern Vanuatu.
  • D. Mweelrea
    Mweelrea is a prominent mountain in County Mayo, Ireland, known as the highest peak in the province of Connacht and a popular destination for hikers.
  • E. Omaruru
    Omaruru is a small historic town in central Namibia known for its colonial-era architecture, vineyards, and role as a local trading and farming 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: Mamfe
Triple: [Southwest Region (Cameroon), containsCity, Mamfe]
Generated description
Mamfe is a town in western Cameroon known as an important local trade and transport hub near the Nigerian border.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mamfe
Target entity description: Mamfe is a town in western Cameroon known as an important local trade and transport hub near the Nigerian border.
  • A. Mumuye
    The Mumuye are an indigenous ethnic group of northeastern Nigeria known for their distinct language and rich artistic traditions, particularly their stylized wooden sculptures.
  • B. Majene
    Majene is a coastal town and regency capital in West Sulawesi, Indonesia, known for its fishing industry and role as a regional administrative center.
  • C. Mwotlap
    Mwotlap is an Oceanic Austronesian language spoken on Mota Lava and nearby islands in northern Vanuatu.
  • D. Mweelrea
    Mweelrea is a prominent mountain in County Mayo, Ireland, known as the highest peak in the province of Connacht and a popular destination for hikers.
  • E. Omaruru
    Omaruru is a small historic town in central Namibia known for its colonial-era architecture, vineyards, and role as a local trading and farming 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_69c0084caac48190a7bc2ad8ba44536f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c069622eb881908b40fc8079d312d6 completed March 22, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6538ca31c8190b4a24662c4eeffe9 completed March 27, 2026, 9:53 a.m.
NEDg Description generation batch_69c6542f23548190a0905c0e2c7341f6 completed March 27, 2026, 9:55 a.m.
NED2 Entity disambiguation (via description) batch_69c654918d9881909f3886ec52a7b00b completed March 27, 2026, 9:57 a.m.
Created at: March 22, 2026, 4:45 p.m.