Triple

T8585710
Position Surface form Disambiguated ID Type / Status
Subject Buganda E203300 entity
Predicate contains P35 FINISHED
Object Kalungu
Kalungu is a district in central Uganda that forms part of the traditional Buganda Kingdom region.
 E746505 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: Kalungu | Statement: [Buganda, contains, Kalungu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kalungu
Context triple: [Buganda, contains, Kalungu]
  • A. Kalangoya
    Kalangoya is an alternative name for the Kalanguya language, an Austronesian language spoken by indigenous communities in the northern Philippines.
  • B. Kalangala
    Kalangala is a town on Uganda’s Ssese Islands in Lake Victoria, serving as the administrative and commercial center of Kalangala District.
  • C. Zalongo
    Zalongo is a historic village and archaeological area in Epirus, Greece, best known for the 19th-century mass suicide of Souliot women commemorated by the Dance of Zalongo.
  • D. Monguno
    Monguno is a town and local government area in Borno State, northeastern Nigeria, known for its strategic location and role in regional security dynamics.
  • E. Kazungula
    Kazungula is a border town in southern Africa, strategically located near the Zambezi River where Botswana, Zambia, Zimbabwe, and Namibia meet, and known for its important regional transport links.
  • 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: Kalungu
Triple: [Buganda, contains, Kalungu]
Generated description
Kalungu is a district in central Uganda that forms part of the traditional Buganda Kingdom region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kalungu
Target entity description: Kalungu is a district in central Uganda that forms part of the traditional Buganda Kingdom region.
  • A. Kalangoya
    Kalangoya is an alternative name for the Kalanguya language, an Austronesian language spoken by indigenous communities in the northern Philippines.
  • B. Kalangala
    Kalangala is a town on Uganda’s Ssese Islands in Lake Victoria, serving as the administrative and commercial center of Kalangala District.
  • C. Zalongo
    Zalongo is a historic village and archaeological area in Epirus, Greece, best known for the 19th-century mass suicide of Souliot women commemorated by the Dance of Zalongo.
  • D. Monguno
    Monguno is a town and local government area in Borno State, northeastern Nigeria, known for its strategic location and role in regional security dynamics.
  • E. Kazungula
    Kazungula is a border town in southern Africa, strategically located near the Zambezi River where Botswana, Zambia, Zimbabwe, and Namibia meet, and known for its important regional transport links.
  • 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_69cebb9716948190b0eb61ddf25fb333 completed April 2, 2026, 6:55 p.m.
NEDg Description generation batch_69cebcdb197881908eeb6c5e4b225a2c completed April 2, 2026, 7 p.m.
NED2 Entity disambiguation (via description) batch_69cebd85ad8481909518afd02dbc5358 completed April 2, 2026, 7:03 p.m.
Created at: March 30, 2026, 6:22 p.m.