Triple

T5948133
Position Surface form Disambiguated ID Type / Status
Subject North Region (Cameroon) E132329 entity
Predicate containsTown P847 FINISHED
Object Bibemi
Bibemi is a town located in the North Region of Cameroon, known as a local administrative and trading center in the area.
 E557643 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: Bibemi | Statement: [North Region (Cameroon), containsTown, Bibemi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bibemi
Context triple: [North Region (Cameroon), containsTown, Bibemi]
  • A. Sameba
    Sameba is the monumental main cathedral of the Georgian Orthodox Church in Tbilisi, renowned as one of the largest religious buildings in the Caucasus.
  • B. Kibushi
    Kibushi is a Bantu language spoken primarily in Mayotte, where it serves as one of the island’s main regional languages.
  • C. Munefusa
    Munefusa is the birth name of Matsuo Bashō, the renowned 17th-century Japanese haiku poet and travel writer.
  • D. Rubeshibe
    Rubeshibe is a district within the city of Kitami in Hokkaido, Japan, known historically as a former town before its merger into the expanded municipality.
  • E. Abemama
    Abemama is a central Pacific atoll in the island nation of Kiribati, known for its lagoon, traditional villages, and role in the country’s colonial and wartime history.
  • 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: Bibemi
Triple: [North Region (Cameroon), containsTown, Bibemi]
Generated description
Bibemi is a town located in the North Region of Cameroon, known as a local administrative and trading center in the area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bibemi
Target entity description: Bibemi is a town located in the North Region of Cameroon, known as a local administrative and trading center in the area.
  • A. Sameba
    Sameba is the monumental main cathedral of the Georgian Orthodox Church in Tbilisi, renowned as one of the largest religious buildings in the Caucasus.
  • B. Kibushi
    Kibushi is a Bantu language spoken primarily in Mayotte, where it serves as one of the island’s main regional languages.
  • C. Munefusa
    Munefusa is the birth name of Matsuo Bashō, the renowned 17th-century Japanese haiku poet and travel writer.
  • D. Rubeshibe
    Rubeshibe is a district within the city of Kitami in Hokkaido, Japan, known historically as a former town before its merger into the expanded municipality.
  • E. Abemama
    Abemama is a central Pacific atoll in the island nation of Kiribati, known for its lagoon, traditional villages, and role in the country’s colonial and wartime history.
  • 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_69c00869d3308190af89b2453e0f7546 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0397c80708190a4778fdb353314b7 completed March 22, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c08d4f0481908547609bc2736380 completed March 23, 2026, 4:24 a.m.
NEDg Description generation batch_69c0c19665b08190ab3c66b7c6c33f61 completed March 23, 2026, 4:29 a.m.
NED2 Entity disambiguation (via description) batch_69c0c4576824819080ced71df8fdda6c completed March 23, 2026, 4:40 a.m.
Created at: March 22, 2026, 4:01 p.m.