Triple

T10172582
Position Surface form Disambiguated ID Type / Status
Subject Serekunda E235366 entity
Predicate hasNeighborhood P40 FINISHED
Object Kanifing
Kanifing is a major urban district within the Greater Banjul area of The Gambia, forming part of the country’s principal commercial and residential center.
 E846070 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: Kanifing | Statement: [Serekunda, hasNeighborhood, Kanifing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kanifing
Context triple: [Serekunda, hasNeighborhood, Kanifing]
  • A. Kandan
    Kandan is a locality within Beijing’s Fengtai District, known primarily as a residential and urban neighborhood area.
  • B. Kandia
    Kandia is a remote valley and settlement area located within Pakistan’s Kohistan mountain ranges, known for its rugged terrain and isolated communities.
  • C. Kankia
    Kankia is a town and local government area in northern Nigeria, known for its role as an administrative and commercial center within Katsina State.
  • D. Kabaena
    Kabaena is an island in Indonesia known for its location off the coast of Sulawesi and its mix of coastal and hilly landscapes.
  • E. Kankanay
    Kankanay is an Austronesian language spoken by the Kankanaey people of the northern Philippines, particularly in the Cordillera region of Luzon.
  • 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: Kanifing
Triple: [Serekunda, hasNeighborhood, Kanifing]
Generated description
Kanifing is a major urban district within the Greater Banjul area of The Gambia, forming part of the country’s principal commercial and residential center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kanifing
Target entity description: Kanifing is a major urban district within the Greater Banjul area of The Gambia, forming part of the country’s principal commercial and residential center.
  • A. Kandan
    Kandan is a locality within Beijing’s Fengtai District, known primarily as a residential and urban neighborhood area.
  • B. Kandia
    Kandia is a remote valley and settlement area located within Pakistan’s Kohistan mountain ranges, known for its rugged terrain and isolated communities.
  • C. Kankia
    Kankia is a town and local government area in northern Nigeria, known for its role as an administrative and commercial center within Katsina State.
  • D. Kabaena
    Kabaena is an island in Indonesia known for its location off the coast of Sulawesi and its mix of coastal and hilly landscapes.
  • E. Kankanay
    Kankanay is an Austronesian language spoken by the Kankanaey people of the northern Philippines, particularly in the Cordillera region of Luzon.
  • 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_69ca84ceafd0819085828600e11bed6b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdec9f6dd8819081588600499165ee completed April 2, 2026, 4:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d30101e3ec819095a587c0dae55f71 completed April 6, 2026, 12:40 a.m.
NEDg Description generation batch_69d30255c7408190a56764f3d3f36ee2 completed April 6, 2026, 12:46 a.m.
NED2 Entity disambiguation (via description) batch_69d30343f4b081909eb80c772f6847bd completed April 6, 2026, 12:50 a.m.
Created at: March 30, 2026, 9:10 p.m.