Triple

T8585713
Position Surface form Disambiguated ID Type / Status
Subject Buganda E203300 entity
Predicate contains P35 FINISHED
Object Gomba
Gomba is a district within the Buganda region of central Uganda, known primarily for its rural communities and agricultural activities.
 E744377 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: Gomba | Statement: [Buganda, contains, Gomba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gomba
Context triple: [Buganda, contains, Gomba]
  • A. Fungo
    Fungo is the costumed team mascot of the New Hampshire Fisher Cats minor league baseball club, entertaining fans at games and community events.
  • B. Tuber
    Tuber is a genus of ectomycorrhizal fungi best known for producing truffles, highly prized edible subterranean fruiting bodies.
  • C. Goba
    Goba is a small Ethiopian town in the Oromia Region that serves as a primary gateway and service center for visitors to Bale Mountains National Park.
  • D. Ganguise
    Ganguise is a watercourse in southern France that feeds the artificial reservoir known as Lac de la Ganguise.
  • E. Gugino
    Gugino is the surname of American actress Carla Gugino, known for her versatile roles in film and television.
  • 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: Gomba
Triple: [Buganda, contains, Gomba]
Generated description
Gomba is a district within the Buganda region of central Uganda, known primarily for its rural communities and agricultural activities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gomba
Target entity description: Gomba is a district within the Buganda region of central Uganda, known primarily for its rural communities and agricultural activities.
  • A. Fungo
    Fungo is the costumed team mascot of the New Hampshire Fisher Cats minor league baseball club, entertaining fans at games and community events.
  • B. Tuber
    Tuber is a genus of ectomycorrhizal fungi best known for producing truffles, highly prized edible subterranean fruiting bodies.
  • C. Goba
    Goba is a small Ethiopian town in the Oromia Region that serves as a primary gateway and service center for visitors to Bale Mountains National Park.
  • D. Ganguise
    Ganguise is a watercourse in southern France that feeds the artificial reservoir known as Lac de la Ganguise.
  • E. Gugino
    Gugino is the surname of American actress Carla Gugino, known for her versatile roles in film and television.
  • 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_69ca8329bb7c8190a63c643730839103 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc457ab8b08190a53c730417288deb completed March 31, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce89c3421881908cfecba9a330b9c7 completed April 2, 2026, 3:22 p.m.
NEDg Description generation batch_69ce8d893cb48190ac5f8a38b21d016c completed April 2, 2026, 3:38 p.m.
NED2 Entity disambiguation (via description) batch_69ce91659b948190ad2c486b5dfa0a94 completed April 2, 2026, 3:55 p.m.
Created at: March 30, 2026, 6:22 p.m.